MBB multipath local aggregation superposition transmission method and system

Abstract

The invention provides an MBB multi-channel local aggregation superposition transmission method and an MBB multi-channel local aggregation superposition transmission system. Belongs to the technical field of communication. The method comprises the following steps that: a plurality of physical links are established in a wireless communication system, and the system selects the plurality of optimal physical links for aggregation according to a current network environment, a current equipment state and a current user demand; dividing data to be transmitted into a plurality of data packets, packaging each data packet according to the characteristics of the selected physical link, and transmitting the packaged data packets in parallel through the selected physical link; in the transmission process, the system monitors the transmission state of each link in real time, and dynamically adjusts the transmission rate and power distribution of each link according to the current network load and equipment state. By transmitting a plurality of physical links in parallel, the network bandwidth can be fully utilized, the data transmission rate is improved, and the transmission delay is reduced.

Description

Technical Field

[0001] The present invention proposes an MBB multi-path local aggregation superposition transmission method and system, belonging to the technical field of communications. Background Art

[0002] With the rapid development of mobile Internet, users have higher and higher requirements for data transmission rate, network stability and power consumption control. Traditional single-channel transmission methods often encounter bandwidth bottlenecks, transmission delays and excessive power consumption when facing complex scenarios such as large data volumes and high concurrent access. Therefore, developing an efficient, stable and low-power MBB multi-channel local aggregation and overlay transmission method has become a technical problem that needs to be solved urgently in the current communication technology field. Summary of the invention

[0003] The present invention provides an MBB multi-path local aggregation overlay transmission method and system to solve the problems mentioned in the above background technology:

[0004] The present invention proposes an MBB multi-path local aggregation overlay transmission method, the method comprising:

[0005] S1. Establish multiple physical links in the wireless communication system. The system selects the optimal multiple physical links for aggregation according to the current network environment, device status and user needs;

[0006] S2, dividing the data to be transmitted into multiple data packets, encapsulating each data packet according to the characteristics of the selected physical link, and transmitting the encapsulated data packets in parallel through the selected physical link;

[0007] S3. During the transmission process, the system monitors the transmission status of each link in real time and dynamically adjusts the transmission rate and power allocation of each link according to the current network load and device status;

[0008] S4. After receiving the data packets from multiple physical links, the receiving end reassembles the data packets according to the link identifiers and timestamps, and verifies the reassembled data.

[0009] Furthermore, the S1 includes:

[0010] S11, scanning available wireless spectrum resources to identify potential physical links; evaluating the signal quality of each potential link; and calculating the correlation between the links;

[0011] S12, real-time monitoring of the status of the device, wherein the status of the device includes battery power, processing capacity, and heat dissipation status;

[0012] S13, analyzing the current user needs of the user, wherein the user needs include data transmission rate, delay requirement, and data priority;

[0013] S14. Based on the above results, multiple optimal physical links are selected for aggregation through a multi-objective optimization algorithm.

[0014] Furthermore, the S2 includes:

[0015] S21, dividing the data to be transmitted into multiple data packets according to the data size, assigning a priority to each data packet, and giving priority to transmitting the data packet with a high priority;

[0016] S22. Add encapsulation information to each data packet according to the characteristics of the selected physical link, where the encapsulation information includes a link identifier, a check code, and a timestamp;

[0017] S23, transmitting the encapsulated data packets in parallel through a multi-channel transmission protocol, and dynamically adjusting the transmission order and rate of the data packets according to the real-time status of each link during the transmission process.

[0018] Furthermore, the S22 includes:

[0019] S221. Collect detailed characteristics of all currently available physical links, where the detailed characteristics include bandwidth, delay, bit error rate, jitter rate, and stability;

[0020] S222, based on the collected link characteristic data, the transmission efficiency of each link is evaluated by a multi-objective optimization algorithm, and a data packet allocation strategy is formulated accordingly;

[0021] S223, based on the dynamic changes of the link, periodically monitor and evaluate the link status, and dynamically adjust the link selection strategy based on the evaluation results;

[0022] S224, adding a link identifier to each data packet so that the data packet can be correctly routed to the target receiving end in a complex network environment;

[0023] S225, generate and add a check code to verify the integrity of the data packet at the receiving end, and detect and correct errors that may occur during the transmission process;

[0024] S226, embed timestamp information, record the time of data packet encapsulation, and assign different priority levels to the data packets according to the priority identifier of the data packets and the business logic or application requirements;

[0025] S227, and based on the existing redundant coding scheme, dynamically adjust the redundancy according to the bit error rate of the link;

[0026] S228. Predict the change trend of link performance in the future by using the link characteristic prediction model, and pre-adjust the encapsulation format and redundancy of the data packet based on the prediction result.

[0027] Furthermore, the S228 includes:

[0028] Extract relevant indicators of each physical link from the historical database, wherein the relevant indicators include bandwidth utilization, delay variation, bit error rate history, jitter rate trend, and stability index;

[0029] The most influential features for link performance prediction are selected through feature selection algorithms and normalized. Model training is performed based on time series analysis, and model parameters are adjusted through cross-validation.

[0030] The current and recent link status data are used as input to the trained prediction model;

[0031] The prediction model outputs relevant prediction values ​​of the link in the future period; the relevant prediction values ​​include bandwidth availability, delay variation range, expected bit error rate and jitter level; and calculates the uncertainty interval of the prediction result;

[0032] Dynamically adjust the packet segment size based on predicted future bandwidth availability and latency, and enable additional error detection and correction mechanisms for links with high bit error rates;

[0033] Based on the prediction of link performance, the routing path of the data packet is optimized, and the redundant coding level in the data packet is dynamically adjusted according to the predicted bit error rate;

[0034] The optimal redundancy configuration is calculated through a redundancy optimization algorithm based on the link characteristic prediction results;

[0035] Through the real-time feedback system, the redundancy strategy is adjusted according to the actual performance of data packet transmission;

[0036] Based on the prediction results, the encapsulation format and redundancy are configured for the data packets to be transmitted. During the data transmission process, the actual link performance is continuously monitored and compared with the prediction results. If there is a deviation, the adaptive adjustment mechanism is immediately triggered to dynamically adjust the data packet encapsulation and redundancy settings.

[0037] Furthermore, the S23 includes:

[0038] S231, configuring the parameters of the parallel transmission protocol, and determining the transmission order of the data packets on the multiple links according to the priority, link status and service requirements of the data packets through the data packet scheduling algorithm;

[0039] S232, and transmit through a multi-channel transmission protocol, during the transmission process, monitor the load and signal quality of each link in real time, evaluate the real-time status of the link based on the real-time monitoring results; based on the evaluation results, dynamically adjust the transmission rate on each link;

[0040] S233, dynamically adjusting the distribution of data packets on multiple links according to the real-time status and transmission requirements of the links through a load balancing algorithm;

[0041] S234. In addition, during the transmission process, the integrity and transmission delay of the data packet are detected using the check code and the timestamp, and the detected erroneous or lost data packets are recovered using a preset error recovery strategy.

[0042] Further, the S232 includes:

[0043] According to the network environment and business requirements, corresponding key parameter settings are performed, and multiple parallel transmission channels are initialized based on the configured parameters;

[0044] Through the link status monitor deployed on each transmission channel, the key performance indicators of the link are collected in real time, including bandwidth utilization, delay and packet loss rate;

[0045] Preprocess the collected raw data and aggregate the preprocessed data to a unified monitoring platform. Build a link status assessment model based on historical data and real-time data. Use the link status assessment model to assess the current status of the link and predict the change trend in the future.

[0046] According to the actual business needs and network environment, set reasonable warning thresholds for various link performance indicators. If a certain indicator is detected to exceed the threshold, the warning mechanism is triggered immediately.

[0047] According to the link status evaluation results, a transmission rate adjustment strategy is designed; based on the adjustment strategy, each channel is adjusted in real time.

[0048] Furthermore, the S3 includes:

[0049] S31, real-time monitoring of key indicators of each link, the key indicators including signal quality, bit error rate and packet loss rate; and improving the accuracy and real-time performance of monitoring through signal processing algorithms during the monitoring process;

[0050] S32. According to the monitoring results, dynamically adjust the transmission rate and power allocation of each link; when the performance of a link degrades, automatically reduce the load of the link or switch to a backup link;

[0051] S33. The data packets are evenly distributed to each link through the load balancing algorithm, and the resource utilization of each link is evaluated in real time.

[0052] Furthermore, the S4 includes:

[0053] S41, the receiving end reassembles the data packets from multiple physical links according to the link identifier and the timestamp, based on the order and integrity of the data packets;

[0054] S42, verifying the reorganized data using a cyclic redundancy check algorithm to detect whether there is data loss or error;

[0055] S43, if a lost or erroneous data packet is detected, recovery is performed through a retransmission mechanism;

[0056] S44, and caches frequently requested data packets through an intelligent caching mechanism.

[0057] The present invention proposes an MBB multi-path local aggregation overlay transmission system, the system comprising:

[0058] Link aggregation module: establishes multiple physical links in the wireless communication system. The system selects the best multiple physical links for aggregation based on the current network environment, device status and user needs;

[0059] Data transmission module: divides the data to be transmitted into multiple data packets, encapsulates each data packet according to the characteristics of the selected physical link, and transmits the encapsulated data packets in parallel through the selected physical link;

[0060] Status monitoring module: During the transmission process, the system monitors the transmission status of each link in real time, and dynamically adjusts the transmission rate and power allocation of each link according to the current network load and device status;

[0061] Data verification module: After receiving data packets from multiple physical links, the receiving end reassembles the data packets according to the link identifier and timestamp, and verifies the reassembled data.

[0062] The invention has the following beneficial effects: by transmitting multiple physical links in parallel, network bandwidth can be fully utilized, data transmission rate can be improved, and transmission delay can be reduced; by real-time monitoring and analysis of network environment, device status and user needs, the aggregation of selected physical links can be made more intelligent and can quickly adapt to network changes; by data packet reorganization, verification and retransmission mechanism, the integrity and reliability of data in the transmission process can be ensured, and data loss caused by link failure can be reduced; by allocating priorities to data packets, important data can be transmitted first, meeting the needs of different application scenarios and improving service quality; by implementing load balancing algorithm, dynamic allocation of data packets between links can be realized, resource utilization can be improved, and overload of some links and idleness of other links can be avoided; by adopting multi-objective optimization algorithm and link characteristic prediction model, the encapsulation format, redundancy and transmission path of data packets can be flexibly adjusted to adapt to different network conditions and business needs; by intelligently caching frequently requested data packets, the burden of repeated transmission can be reduced and the system response speed can be improved; by real-time monitoring and dynamic adjustment of performance indicators of each link, efficient utilization of links can be achieved, and optimization of overall network performance can be ensured; by reducing delay, improving transmission rate and ensuring data integrity, user experience in different scenarios can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 It is a step diagram of the method of the present invention;

[0064] Figure 2 This is a system module diagram of the present invention. DETAILED DESCRIPTION

[0065] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0066] One embodiment of the present invention, as Figure 1 As shown, a method for MBB multi-path local aggregation overlay transmission includes:

[0067] S1. Establish multiple physical links in the wireless communication system. The system selects the optimal multiple physical links for aggregation according to the current network environment, device status and user needs;

[0068] S2, dividing the data to be transmitted into multiple data packets, encapsulating each data packet according to the characteristics of the selected physical link, and transmitting the encapsulated data packets in parallel through the selected physical link;

[0069] S3. During the transmission process, the system monitors the transmission status of each link in real time and dynamically adjusts the transmission rate and power allocation of each link according to the current network load and device status;

[0070] S4. After receiving data packets from multiple physical links, the receiving end reassembles the data packets according to the link identifier and timestamp, and verifies the reassembled data to detect whether there is data loss or error; for lost or erroneous data, the system attempts to recover through a retransmission mechanism.

[0071] The working principle of the above technical solution is as follows: In a wireless communication system, multiple physical links are first established as channels for data transmission. The system selects the optimal multiple physical links for aggregation according to factors such as the current network environment (such as signal strength, interference), device status (such as transmission power, receiving sensitivity) and user needs (such as data transmission rate, reliability requirements), for example, the one with the strongest signal, the highest receiving sensitivity and the highest transmission rate. The data to be transmitted is divided into multiple data packets, each of which is encapsulated according to the characteristics of the selected physical link, including adding link identification, timestamp and other information. The encapsulated data packets are transmitted in parallel through the selected physical link, thereby making full use of the bandwidth resources of multiple links. During the transmission process, the system monitors the transmission status of each link in real time, including key indicators such as signal quality, bit error rate, and packet loss rate. According to the current network load and device status, the system dynamically adjusts the transmission rate and power allocation of each link. After receiving the data packets from multiple physical links, the receiving end reassembles the data packets according to the link identification and timestamp. The reassembled data is checked to detect whether there is data loss or error. For lost or erroneous data, the system attempts to recover through the retransmission mechanism to ensure the reliability of data transmission.

[0072] The effect of the above technical solution is: by establishing multiple physical links and aggregating them, parallel data transmission is realized. Compared with single link transmission, the data transmission rate and throughput can be significantly improved. The system can select the optimal multiple physical links for aggregation according to the current network environment, device status and user needs, ensuring that data transmission is always carried out on the best link, thereby improving transmission efficiency. During the transmission process, the system monitors the transmission status of each link in real time, including key indicators such as signal quality, bit error rate, and packet loss rate. According to these indicators, the system can dynamically adjust the transmission rate and power allocation of each link to ensure the stability and reliability of data transmission. After the receiving end receives data packets from multiple physical links, it reassembles the data packets according to the link identifier and timestamp. At the same time, the reassembled data is checked to detect whether there is data loss or error. For lost or erroneous data, the system attempts to recover through a retransmission mechanism, thereby further enhancing the reliability of data transmission. The system can dynamically adjust the transmission rate of each link according to the current network load and device status. The flexible adjustment mechanism can ensure that when the network load is high, the transmission rate is reduced to avoid network congestion; when the network load is low, the network resources are fully utilized by increasing the transmission rate. In addition to the transmission rate, the system can also dynamically adjust the power allocation of each link to ensure that the power of each link is reasonably allocated during the transmission process, thereby improving energy efficiency and reducing energy consumption. It can be dynamically adjusted according to user needs to meet the different needs of different users for data transmission rate, reliability and stability. The above technical solution can be widely used in various wireless communication scenarios, such as video conferencing, online games, high-definition video transmission, etc. By improving data transmission efficiency and reliability, the above technical solution can significantly improve the user's service quality experience. For example, in video conferencing, users can enjoy a smoother and clearer video call experience; in online games, users can enjoy lower latency and higher game stability.

[0073] In one embodiment of the present invention, the S1 includes:

[0074] S11. Scan the available wireless spectrum resources to identify all potential physical links; evaluate the signal quality of each potential link, including indicators such as signal strength, stability, and interference level; and calculate the correlation between the links; wherein the signal quality is evaluated by the following formula:

[0075]

[0076] Where S represents the current signal strength; S y The signal strength threshold is used to determine whether the signal strength is sufficient; k 1 and k 2represents the shape parameter, which is used to adjust the steepness of the logarithmic and exponential functions; N represents the number of interference sources or the number of data points in the time window; H i represents the signal stability in the i-th time window or scenario; G j represents the interference degree of the jth interference source; w 1 , w 2 , w 3 represents the weight coefficient and the sum is 1;

[0077] S12, real-time monitoring of the status of the device, wherein the status of the device includes battery power, processing capacity, and heat dissipation status;

[0078] S13, analyzing the current user needs of the user, wherein the user needs include data transmission rate, delay requirement, and data priority;

[0079] S14. Based on the above results, multiple optimal physical links are selected for aggregation through a multi-objective optimization algorithm.

[0080] The working principle of the above technical solution is as follows: a spectrum analysis tool or device is used to comprehensively search the available wireless spectrum in the surrounding environment to identify all potential physical links. The signal quality of each potential link is evaluated, including the measurement of indicators such as signal strength, stability, and interference level. The correlation between links is calculated by considering factors such as the relative position and obstacles between devices. The correlation between links may vary due to factors such as the device location, the obstruction of environmental obstacles, and the propagation characteristics of wireless signals. Highly correlated links may have mutual influence on transmission performance, so they need to be considered when selecting links; real-time monitoring of devices participating in link aggregation, including battery power, processing power, and heat dissipation conditions. Ensuring that the selected link does not exceed the physical limitations of the device, such as power and bandwidth, can avoid link performance degradation or failure due to insufficient device capabilities; in-depth analysis of the user's current data transmission rate, delay requirements, and data priority requirements. According to user needs, links that can meet these requirements are selected for aggregation. For example, if the user requires a high data transmission rate, a multi-objective optimization algorithm is used to select the optimal multiple physical links for aggregation based on the above scanning, evaluation, and monitoring results. When selecting links, consider the complementarity between links, such as the diversity of frequency bands, modulation methods, and coding technologies. Determine the link aggregation strategy based on the algorithm results, including which links to aggregate and how to allocate transmission tasks.

[0081] The effect of the above technical solution is: by comprehensively scanning the available wireless spectrum resources, the technical solution can identify all potential physical links, thereby ensuring the maximum utilization of wireless resources. Signal quality evaluation of each potential link helps to screen out links with good signal quality and high stability, providing strong guarantee for subsequent link aggregation. Considering factors such as the relative position and obstacles between devices and calculating the correlation between links can help avoid selecting highly correlated links, thereby reducing interference and mutual influence between links and improving the overall transmission performance and stability after link aggregation. Real-time monitoring of the battery power, processing power and heat dissipation status of the device can timely discover possible problems and hidden dangers of the device, ensure that the selected link does not exceed the physical limitations of the device, thereby protecting the normal operation of the device and extending its service life. According to the changes in the device status, the technical solution can flexibly adjust the link selection strategy to adapt to the needs of different scenarios, ensuring that the transmission performance after link aggregation is always maintained in the optimal state. In-depth analysis of the user's current data transmission rate, delay requirements and data priority helps to accurately grasp the user's specific needs and ensure that the transmission performance after link aggregation can meet the user's actual needs. According to the changes in user needs, this technical solution can dynamically adjust the link aggregation strategy to provide personalized services and improve user satisfaction and loyalty. Through the multi-objective optimization algorithm, this technical solution can select the best multiple physical links for aggregation to ensure that the transmission performance after link aggregation is maximized. When selecting links, full consideration is given to the complementarity between links, such as the diversity of frequency bands, modulation methods, and coding technologies, to improve the overall performance and stability after link aggregation and reduce the risk of overall performance degradation caused by a single link failure.The above signal quality evaluation formula comprehensively considers the main factors affecting signal quality by introducing signal strength (S), signal stability (H) and interference level (G), making the evaluation result more comprehensive and accurate. The weight coefficients (w1, w2, w3) allow the influence of each factor to be adjusted according to the actual application scenario, providing flexibility. The shape parameters (k1, k2) allow the steepness of the evaluation formula to be adjusted according to different environments and needs, and can adapt to changes in signal conditions, such as providing more stringent signal quality evaluation in high-interference environments. By setting the signal strength threshold, the formula can effectively determine whether the signal is strong enough, thereby affecting the link selection. The introduction of signal stability and interference source considerations helps to better identify unstable links and reduce transmission errors caused by interference, thereby Improve the reliability of link selection. When selecting multiple physical links, the correlation between different links can be calculated through signal quality evaluation results, and the link combination strategy can be optimized to ensure the efficiency of data transmission. Combined with the specific needs of users (such as data transmission rate, delay requirements and data priority), signal quality evaluation can provide users with the best link selection and improve the data transmission experience. Through the multi-objective optimization algorithm, according to different user needs and network conditions, the best physical link is selected for aggregation to ensure the rational use of resources. The battery power, processing power and heat dissipation of the device are monitored in real time. The link selection strategy can be adjusted in time to avoid the degradation of signal quality due to poor device status. Based on real-time feedback information, the link selection can be dynamically optimized to improve the flexibility and responsiveness of the network. Through the above formula, the evaluation of signal quality can not only improve the scientificity and rationality of link selection, but also greatly enhance the adaptability of wireless communication systems under different environments and needs, thereby optimizing the overall user experience.

[0082] In one embodiment of the present invention, the S2 includes:

[0083] S21, dividing the data to be transmitted into multiple data packets according to the data size, assigning a priority to each data packet, and giving priority to transmitting the data packet with a high priority;

[0084] S22. Add encapsulation information to each data packet according to the characteristics of the selected physical link, where the encapsulation information includes a link identifier, a check code, and a timestamp;

[0085] S23, the encapsulated data packets are transmitted in parallel through a multi-channel transmission protocol, and during the transmission process, the transmission order and rate of the data packets are dynamically adjusted according to the real-time status of each link (such as load, signal quality, etc.).

[0086] The working principle of the above technical solution is as follows: first, the data to be transmitted is divided into multiple data packets according to the size of the data. It ensures that the data can be efficiently transmitted on different physical links, and it is convenient to manage and monitor each data packet independently; each data packet is assigned a priority based on factors such as the urgency, importance or user-specified priority of the data. By assigning priorities to data packets, it can be ensured that the most important data is transmitted first when resources are limited; and data packets with high priority are transmitted first. According to the characteristics of the selected physical link (such as bandwidth, delay, bit error rate, etc.), encapsulation information is added to each data packet; the encapsulation information includes a link identifier (used to identify the link to which the data packet belongs), a checksum (used to detect whether an error occurs during the transmission of the data packet) and a timestamp (used to record the sending time of the data packet); in the encapsulation process, the redundancy of the data packet also needs to be considered. Redundancy refers to the amount of additional information added to the data packet, which is used to deal with potential transmission errors. The encapsulation process is to combine the data packet with the encapsulation information to form a complete transmission unit. The encapsulated data packet is transmitted in parallel through a multi-channel transmission protocol. During the transmission process, the transmission order and rate of the data packet are dynamically adjusted according to the real-time status of each link (such as load, signal quality, etc.). The dynamic adjustment mechanism ensures that when the link status changes, the transmission strategy can be adjusted in time to adapt to the new transmission environment; by adjusting the transmission order and rate of data packets, the transmission performance can be optimized. For example, when the link load is high, high-priority data packets can be transmitted first and the transmission rate of other data packets can be reduced; when the link signal quality is poor, the redundancy of the data packet can be increased or a more reliable transmission path can be selected.

[0087] The effect of the above technical solution is: by dividing the data to be transmitted into multiple data packets, the size of each data packet can be made more suitable for the transmission capacity of the selected physical link, thereby improving the transmission efficiency. Prioritizing the transmission of high-priority data packets can ensure that key data can reach the destination faster, reduce waiting time, and further improve the overall transmission efficiency. The use of multi-channel transmission protocols for parallel transmission can make full use of the bandwidth resources of multiple physical links to achieve rapid data transmission. Parallel transmission can also reduce the risk of transmission interruption caused by a single link failure and improve the reliability of transmission. By adding encapsulation information such as link identification, checksum and timestamp to each data packet, the integrity and accuracy of the data packet during transmission can be ensured. The checksum can be used to detect whether an error occurs in the data packet during transmission, and the timestamp can be used to record the sending and receiving time of the data packet, which is convenient for subsequent data processing and analysis. Considering the redundancy of the data packet during the encapsulation process can increase the error resistance of the data packet and reduce the risk of data loss. Redundancy can be achieved by adding additional data blocks or checksum information to ensure that even if part of the data is lost or erroneous during transmission, the original data can be restored through redundant information. During the transmission process, the transmission order and rate of data packets can be dynamically adjusted according to the real-time status of each link (such as load, signal quality, etc.), which can optimize the utilization of resources. For example, when the link load is high, high-priority data packets can be transmitted first, and the transmission rate of other data packets can be appropriately reduced to avoid network congestion; when the link signal quality is poor, the redundancy of the data packet can be increased or a more reliable transmission path can be selected to improve the transmission success rate. This technical solution can add encapsulation information and adjust the transmission strategy according to different physical link characteristics (such as bandwidth, delay, bit error rate, etc.), so as to adapt to the data transmission requirements under different link environments, and can maintain efficient and reliable transmission performance in a variety of network environments. Through mechanisms such as priority transmission and parallel transmission, the time users wait for data transmission to complete can be reduced, and the user experience can be improved. By increasing the redundancy of data packets and dynamically adjusting transmission strategies, the success rate of data transmission can be improved, and problems such as data loss or delay caused by transmission errors or network failures can be reduced.

[0088] In one embodiment of the present invention, the S22 includes:

[0089] S221. Collect detailed characteristics of all currently available physical links, where the detailed characteristics include bandwidth, delay, bit error rate, jitter rate, and stability;

[0090] S222, based on the collected link characteristic data, the transmission efficiency of each link is evaluated by a multi-objective optimization algorithm, and a data packet allocation strategy is formulated accordingly;

[0091] S223, based on the dynamic changes of the link (such as network congestion, equipment failure), periodic link status monitoring and evaluation are performed, and the link selection strategy is dynamically adjusted based on the evaluation results;

[0092] S224, adding a link identifier to each data packet so that the data packet can be correctly routed to the target receiving end in a complex network environment;

[0093] S225, generate and add a check code to verify the integrity of the data packet at the receiving end, and detect and correct errors that may occur during the transmission process;

[0094] S226, embed timestamp information, record the time of data packet encapsulation, and assign different priority levels to the data packets according to the priority identifier of the data packets and the business logic or application requirements;

[0095] S227, and based on the existing redundant coding scheme, dynamically adjust the redundancy according to the bit error rate of the link; wherein the bit error rate is calculated by the following formula:

[0096]

[0097] Where T is the total monitoring time; R is the transmission rate; M is the number of independent time intervals recorded during the monitoring period; E i represents the number of error bits received in the i-th time interval; t i represents the start time of the i-th time interval; λ represents the time attenuation factor of the bit error rate, which is used to reduce the impact of errors in the past time interval;

[0098] S228. Predict the change trend of link performance in the future by using the link characteristic prediction model, and pre-adjust the encapsulation format and redundancy of the data packet based on the prediction result.

[0099] The working principle of the above technical solution is as follows: the system first collects detailed characteristics of all currently available physical links. The key indicators include bandwidth, delay, bit error rate, jitter rate and stability. Based on the collected link characteristic data, the system evaluates the transmission efficiency of each link through a multi-objective optimization algorithm. The evaluation results will serve as the basis for the data packet allocation strategy. Considering the possible dynamic changes of the link (such as network congestion, equipment failure, etc.), the system performs periodic link status monitoring and evaluation. The monitoring results will be used to dynamically adjust the link selection strategy to adapt to the changes in link status. Add a link identifier to each data packet. The link identifier is the "identity card" of the data packet transmitted in the network, ensuring that the data packet can reach the predetermined destination accurately. The system generates and attaches a checksum to the data packet for verifying the integrity of the data packet at the receiving end. The checksum can detect and correct errors that may occur during the transmission process to ensure the accuracy of the data. The timestamp information is embedded in the data packet to record the encapsulation time of the data packet. According to the priority identifier of the data packet, the system assigns different priority levels to the data packet according to the business logic or application requirements. The timestamp and priority identifier help the receiving end to process and prioritize the data packets in an orderly manner. Based on the existing redundant coding scheme, the system dynamically adjusts the redundancy of the data packet according to the bit error rate of the link. By increasing or decreasing redundant information, the system can ensure the error resistance of the data packet during transmission and reduce the risk of data loss. Using the link characteristic prediction model, the system predicts the trend of link performance changes in the future. Based on the prediction results, the system pre-adjusts the encapsulation format and redundancy of the data packet to adapt to changes in link performance.

[0100] The effect of the above technical solution is: by collecting detailed characteristics of all currently available physical links, including bandwidth, delay, bit error rate, etc., the system can more accurately understand the transmission capacity of each link. Based on these characteristic data, the transmission efficiency of the link is evaluated through a multi-objective optimization algorithm, and a data packet allocation strategy is formulated to ensure that the data packet is allocated to the link with the highest transmission efficiency, thereby improving the transmission efficiency. The system can periodically monitor the link status and dynamically adjust the link selection strategy according to the evaluation results to adapt to the dynamic changes that may exist in the link (such as network congestion, equipment failure), avoid sending data packets to links with poor performance, thereby further improving the transmission efficiency and resource utilization. Adding a link identifier to each data packet can ensure that the data packet is correctly routed to the target receiving end in a complex network environment, reducing the risk of data packet loss. Generating and attaching a checksum can verify the integrity of the data packet at the receiving end, detect and correct errors that may occur during the transmission process, thereby improving the reliability of data transmission. The system can dynamically adjust the redundancy of the data packet according to the bit error rate of the link to ensure the error resistance of the data packet during transmission. By increasing or reducing redundant information, the system can improve the stability and reliability of data transmission while ensuring transmission efficiency. By embedding timestamp information, the encapsulation time of the data packet can be recorded, which helps the receiving end to process the data packet in an orderly manner. According to the priority identification of the data packet, the system can assign different priority levels to the data packet according to the business logic or application requirements, thereby optimizing the flexibility of data transmission, ensuring that key data can reach the destination faster, and improving the overall transmission efficiency. Through the link characteristic prediction model, the system can predict the changing trend of link performance in the future. Based on the prediction results, the system can pre-adjust the encapsulation format and redundancy of the data packet to adapt to the change of link performance. The above bit error rate formula can more accurately reflect the bit error situation of the link by considering the number of error bits and their time distribution in multiple time intervals. Especially in the network environment, the link status may change due to instantaneous fluctuations; by introducing the time decay factor λ, the impact of the bit error in the earlier time period on the current BER is gradually weakened, which can reduce the interference of historical data on the current performance evaluation and pay more attention to the real-time performance of the link. Based on the calculation of BER, the system can adjust the redundancy of the redundant coding scheme according to the real-time network status. When the bit error rate is detected to rise, the system can increase the redundancy to improve the reliability of data transmission, and vice versa, it can reduce the redundancy to improve the transmission efficiency. By evaluating link characteristics (including BER) and combining it with a multi-objective optimization algorithm, a more reasonable data packet allocation strategy can be formulated to improve overall network performance, reduce latency and jitter, and ensure the reliability of data transmission. As an important indicator for link status monitoring, once an abnormal increase in the bit error rate is found, the system can quickly identify possible link failures and take measures to recover them, avoiding data loss or affecting subsequent data transmission.As network conditions change, the system can adapt to changes in network status in real time through the calculation results of this formula. Through periodic link status monitoring, the link selection strategy can be adjusted in time to achieve the best data transmission performance. Through the application of this bit error rate formula, the network management system can more accurately and flexibly evaluate and optimize link performance, thereby effectively improving the transmission efficiency and stability of the network.

[0101] In one embodiment of the present invention, the S228 includes:

[0102] Extract relevant indicators of each physical link from the historical database, wherein the relevant indicators include bandwidth utilization, delay variation, bit error rate history, jitter rate trend, and stability index;

[0103] The most influential features for link performance prediction are selected through feature selection algorithms and normalized. Model training is performed based on time series analysis, and model parameters are adjusted through cross-validation.

[0104] The current and recent (e.g., the past week) link status data (including bandwidth usage, latency measurements, bit error rate detection, etc.) are used as input into the trained prediction model;

[0105] The prediction model outputs relevant prediction values ​​of the link within a period of time in the future (such as the next 1 hour, 24 hours, etc.); the relevant prediction values ​​include bandwidth availability, delay variation range, expected bit error rate and jitter level; and calculates the uncertainty interval of the prediction result;

[0106] Dynamically adjust the packet segment size based on predicted future bandwidth availability and latency, and enable additional error detection and correction mechanisms for links that are expected to have higher bit error rates;

[0107] Based on the prediction of link performance, the routing path of the data packet is optimized, and the link combination with better expected performance is selected to avoid potential bottlenecks or unstable links. According to the predicted bit error rate, the redundant coding level in the data packet (such as increasing or decreasing the length of the error correction code) is dynamically adjusted to balance the reliability of data transmission and bandwidth efficiency;

[0108] The optimal redundancy configuration is calculated through a redundancy optimization algorithm based on the link characteristic prediction results;

[0109] Through the real-time feedback system, the redundancy strategy is adjusted according to the actual performance of data packet transmission (such as successful reception rate, number of retransmissions, etc.);

[0110] Based on the prediction results, the appropriate encapsulation format and redundancy are configured in advance for the data packets to be transmitted. During the data transmission process, the actual link performance is continuously monitored and compared with the prediction results. If there is a deviation, the adaptive adjustment mechanism is immediately triggered to dynamically adjust the data packet encapsulation and redundancy settings.

[0111] The working principle of the above technical solution is: extract relevant indicators of each physical link from the historical database, including bandwidth utilization, delay variation, bit error rate history, jitter rate trend and stability index. Use feature selection algorithm (such as Lasso regression, random forest feature importance evaluation) to screen out the most influential features for link performance prediction and perform normalization. Model training is performed based on time series analysis, and model parameters are adjusted through cross-validation to optimize prediction performance. The trained prediction model can receive current and recent link status data as input and output relevant prediction values ​​of the link in the future. The prediction model outputs relevant prediction values ​​of the link in the future (such as the next 1 hour, 24 hours, etc.), including bandwidth availability, delay variation range, expected bit error rate and jitter level. The uncertainty interval of the prediction result is calculated to quantify the reliability of the prediction result and provide a basis for subsequent decision-making. According to the predicted future bandwidth availability and delay, the segmentation size of the data packet is dynamically adjusted to optimize the transmission efficiency. For links with expected high bit error rates, additional error detection and correction mechanisms are enabled to improve the reliability of data transmission. Based on the predicted results of link performance, the routing path of the data packet is optimized, and the link combination with better expected performance is selected to avoid potential bottlenecks or unstable links. According to the predicted bit error rate, the redundant coding level in the data packet is dynamically adjusted to balance the reliability and bandwidth efficiency of data transmission. The optimal redundancy configuration is calculated by comprehensively considering the bit error rate, delay and bandwidth limitations through the redundancy optimization algorithm based on the predicted results of link characteristics. Using the real-time feedback system, the redundancy strategy is adjusted according to the actual performance of the data packet transmission (such as the successful reception rate, the number of retransmissions, etc.) to achieve more refined transmission control. During the data transmission process, the actual link performance is continuously monitored and compared with the predicted results. If there is a deviation, the adaptive adjustment mechanism is immediately triggered to dynamically adjust the packet encapsulation and redundancy settings to cope with the changes in link performance.

[0112] The effect of the above technical solution is: by extracting relevant indicators from the historical database, and using the feature selection algorithm to screen out the most influential features, and then combining time series analysis for model training, it is possible to achieve accurate prediction of link performance, so that the system can understand in advance the key information such as bandwidth availability, delay variation range, expected bit error rate and jitter level of the link in the future. According to the predicted future bandwidth availability and delay, the system can dynamically adjust the size of the data packet segmentation to optimize the transmission efficiency. When the bandwidth is sufficient and the delay is low, the data packet segmentation size can be appropriately increased to increase the transmission speed; otherwise, the data packet segmentation size can be reduced to reduce the transmission delay and error rate. For links that are expected to have a higher bit error rate, the system can enable additional error detection and correction mechanisms, such as increasing the length of the error correction code or adopting a more complex coding scheme to improve the reliability of data transmission. Based on the prediction results of link performance, the system can select a link combination with better expected performance for data packet transmission, thereby avoiding potential bottlenecks or unstable links and reducing the loss and delay of data packets during transmission. According to the predicted bit error rate, the system can dynamically adjust the level of redundant coding in the data packet to balance the reliability of data transmission and bandwidth efficiency. When the bit error rate is high, the redundant coding level is increased to improve the reliability of data transmission; when the bit error rate is low, the redundant coding level is reduced to save bandwidth resources. The algorithm can comprehensively consider multiple factors such as bit error rate, delay and bandwidth limitation, calculate the optimal redundancy configuration, so that the system can automatically adjust the redundancy settings according to the changes in link characteristics, thereby improving the system's adaptability and intelligence level. Through the real-time feedback system, the system can adjust the redundancy strategy according to the actual performance of data packet transmission (such as successful reception rate, number of retransmissions, etc.), so that the system can promptly discover and solve problems in the transmission process, and further improve the reliability and stability of data transmission. During the data transmission process, the system can continuously monitor the actual performance of the link and compare it with the predicted results. If there is a deviation, the adaptive adjustment mechanism is immediately triggered to dynamically adjust the packet encapsulation and redundancy settings to adapt to the changes in link characteristics. By accurately predicting link performance and dynamically adjusting the transmission strategy, the system can reduce unnecessary bandwidth waste and retransmission times, thereby reducing operating costs. At the same time, since the system has a high level of adaptability and intelligence, it can reduce the number of manual interventions and troubleshooting, and reduce maintenance costs.

[0113] In one embodiment of the present invention, the S23 includes:

[0114] S231, configuring the parameters of the parallel transmission protocol, and determining the transmission order of the data packets on the multiple links according to the priority, link status and service requirements of the data packets through the data packet scheduling algorithm;

[0115] S232, and transmit through a multi-channel transmission protocol, during the transmission process, monitor the load and signal quality of each link in real time, evaluate the real-time status of the link based on the real-time monitoring results; based on the evaluation results, dynamically adjust the transmission rate on each link;

[0116] S233, dynamically adjusting the distribution of data packets on multiple links according to the real-time status and transmission requirements of the links through a load balancing algorithm;

[0117] S234. In addition, during the transmission process, the integrity and transmission delay of the data packet are detected using the check code and the timestamp, and the detected erroneous or lost data packets are recovered using a preset error recovery strategy.

[0118] The working principle of the above technical solution is as follows: First, it is necessary to configure the relevant parameters of the parallel transmission protocol, including the packet fragmentation size, retransmission strategy and flow control mechanism. Through the packet scheduling algorithm, the system can dynamically determine the transmission order of the data packet on multiple links according to the priority of the data packet, the link status and the service requirements. Using the multi-channel transmission protocol, data can be transmitted in parallel on multiple links; during the transmission process, the system will monitor the load and signal quality of each link in real time, including key indicators such as bandwidth utilization, delay, and packet loss rate. Based on the evaluation results of the link status, the system will dynamically adjust the transmission rate on each link to optimize the transmission performance. For example, on a link with high bandwidth utilization, the transmission rate can be appropriately reduced to reduce the possibility of congestion and packet loss; through the load balancing algorithm, the system can dynamically adjust the distribution of data packets on multiple links according to the real-time status of the link and the transmission requirements. This adjustment is intended to achieve a balanced distribution of traffic and avoid the situation where some links are overloaded while other links are idle; in actual applications, the load balancing algorithm will dynamically adjust the data packet allocation strategy based on the link status information monitored in real time. For example, when the delay or packet loss rate of a link suddenly increases, the algorithm will quickly reduce the number of data packets assigned to the link to ensure the overall quality of data transmission; during the transmission process, the system will use checksums and timestamps to detect the integrity and transmission delay of the data packet. The checksum is used to verify whether the data packet has errors or damage during transmission, while the timestamp is used to measure the transmission delay of the data packet; for detected errors or lost data packets, the system will recover through preset error recovery strategies, including retransmission mechanism, error correction coding, etc. The retransmission mechanism means that when a data packet is lost or erroneous, the system will resend the data packet to ensure data integrity; and error correction coding is a technology that embeds redundant information in data packets to detect and correct transmission errors.

[0119] The effects of the above technical solutions are as follows: by reasonably configuring the parameters of the parallel transmission protocol, such as the packet fragmentation size, retransmission strategy and flow control mechanism, the data transmission process can be optimized, unnecessary waiting and retransmission can be reduced, and thus the transmission efficiency can be improved; the packet scheduling algorithm can dynamically adjust the transmission order of data packets on multiple links to adapt to the real-time changes in the network environment and ensure the stability and reliability of data transmission, especially when the network conditions are unstable; the multi-channel transmission protocol allows data to be transmitted in parallel on multiple links, thereby making full use of network resources and improving the overall transmission capacity; by real-time monitoring of the load and signal quality of each link, the system can promptly discover and solve potential network bottlenecks or problems. Dynamically adjusting the transmission rate based on the evaluation results helps to balance the network load and avoid congestion and packet loss; the load balancing algorithm can dynamically adjust the distribution of data packets on multiple links according to the real-time status and transmission requirements of the link, which helps to optimize the network traffic distribution and improve the overall performance of the system; through load balancing, the system can avoid over-reliance on a single link, thereby reducing the risk of single point failure. Even if a link fails, other links can continue to transmit data to ensure the continuous and stable operation of the system; by using checksums and timestamps to detect the integrity and transmission delay of data packets, errors or damaged data packets in the transmission process can be discovered and corrected in a timely manner to ensure data accuracy and reliability; through preset error recovery strategies (such as retransmission, error correction coding, etc.), the system can automatically recover lost or erroneous data packets, thereby improving the quality of data transmission and reducing the risk of system downtime or data loss due to data transmission errors.

[0120] In one embodiment of the present invention, the S232 includes:

[0121] According to the network environment and business requirements, corresponding key parameter settings are performed, and multiple parallel transmission channels are initialized based on the configured parameters;

[0122] Through the link status monitor deployed on each transmission channel, the key performance indicators of the link are collected in real time, including bandwidth utilization, delay and packet loss rate;

[0123] Preprocess the collected raw data and aggregate the preprocessed data to a unified monitoring platform. Build a link status assessment model based on historical data and real-time data. Use the link status assessment model to assess the current status of the link and predict the change trend in the future.

[0124] According to the actual business needs and network environment, set reasonable warning thresholds for various link performance indicators. If a certain indicator is detected to exceed the threshold, the warning mechanism is triggered immediately.

[0125] According to the link status evaluation results, a transmission rate adjustment strategy is designed; based on the adjustment strategy, each channel is adjusted in real time.

[0126] The working principle of the above technical solution is as follows: according to the network environment and business requirements, the packet fragment size, retransmission strategy (such as exponential backoff, limited number of retransmissions, etc.) and flow control mechanism (such as sliding window protocol) are configured. Based on the configured parameters, multiple parallel transmission channels are initialized. The establishment of parallel transmission channels allows data to be transmitted simultaneously on multiple links. A link status monitor is deployed on each transmission channel to collect key performance indicators of the link in real time, including bandwidth utilization, delay and packet loss rate. The collected raw data is preprocessed, such as denoising and normalization, and the preprocessed data is aggregated to a unified monitoring platform for centralized management and analysis. A link status evaluation model is constructed based on historical data and real-time data. Through the link status evaluation model, the current state of the link is evaluated and the change trend in the future is predicted. According to the actual business requirements and network environment, reasonable warning thresholds are set for each performance indicator of the link. If a certain indicator is monitored to exceed the threshold, the warning mechanism is immediately triggered to notify relevant personnel to take corresponding measures. According to the link status evaluation results, a transmission rate adjustment strategy is designed. When it is detected that the link bandwidth utilization is too high, the transmission rate is reduced to reduce congestion; when the link delay increases, the transmission efficiency is optimized by adjusting the packet fragment size or retransmission strategy. Based on the transmission rate adjustment strategy, each channel is adjusted in real time. Real-time adjustment can ensure that the transmission efficiency and quality of data on different links are optimized.

[0127] The effects of the above technical solutions are as follows: by setting key parameters such as data packet fragmentation size, retransmission strategy and flow control mechanism according to network environment and business requirements, the system can flexibly adapt to different network conditions and application scenarios; initializing multiple parallel transmission channels improves the flexibility and reliability of data transmission, and even if some links fail, other links can continue to transmit data; through the link status monitor deployed on each transmission channel, key performance indicators such as bandwidth utilization, delay and packet loss rate are collected in real time, providing the system with comprehensive link status information; the link status evaluation model constructed based on historical data and real-time data can accurately evaluate the current status of the link and predict the trend of changes in the future, providing strong support for system optimization; setting reasonable warning thresholds for various performance indicators of the link Once a certain indicator is monitored to exceed the threshold, the early warning mechanism is immediately triggered to remind relevant personnel to take timely measures to avoid potential network problems; by adjusting the transmission rate, data packet fragment size or retransmission strategy in real time, the system can quickly respond to network changes and ensure the stability and efficiency of data transmission; according to the link status evaluation results, the transmission rate is dynamically adjusted to avoid network congestion and improve data transmission efficiency; by adjusting the data packet fragment size and retransmission strategy, the system can more reasonably utilize network resources and reduce unnecessary transmission overhead and delay; through real-time link status monitoring and adjustment, the system can ensure stable data transmission and reduce transmission interruptions or delays caused by network problems; optimized transmission efficiency and resource utilization provide users with higher quality data transmission services and improve user experience.

[0128] In one embodiment of the present invention, the S233 includes:

[0129] During the transmission process, the real-time status information of each link is continuously collected, including bandwidth utilization, delay, jitter, packet loss rate and link stability, and the collected information is pre-processed;

[0130] Based on historical data and real-time data, a link performance evaluation model is constructed, and a comprehensive performance score of the link is given by comprehensively considering multiple performance indicators of the link through the link performance evaluation model;

[0131] According to the performance evaluation results of the links, the distribution of data packets on multiple links is dynamically adjusted through the load balancing algorithm;

[0132] After the data packet allocation is adjusted, the load and transmission performance of each link are continuously monitored, and a feedback mechanism is established to feed the monitoring results back to the load balancing algorithm in real time, so as to make fine adjustments based on the actual situation.

[0133] The working principle of the above technical solution is as follows: during the data transmission process, the system continuously collects the real-time status information of each link, including key performance indicators such as bandwidth utilization, delay, jitter, packet loss rate and link stability; the collected raw data is preprocessed, and the system combines historical data and real-time data to build a link performance evaluation model. Historical data provides the long-term trend and benchmark of link performance, while real-time data reflects the current link status; the link performance evaluation model comprehensively considers multiple performance indicators of the link, such as bandwidth utilization, delay, jitter, packet loss rate and link stability. These indicators jointly determine the comprehensive performance score of the link; based on the link performance evaluation results, the system can identify links with better performance and links with worse performance; based on the load balancing algorithm, the system dynamically adjusts the distribution of data packets on multiple links. Links with better performance will undertake more data transmission tasks, while links with worse performance will reduce the amount of data transmission accordingly; after the data packet distribution is adjusted, the system continuously monitors the load and transmission performance of each link to discover and solve potential transmission problems; the system has established a feedback mechanism to feed back the monitoring results to the load balancing algorithm in real time. Based on the feedback results, the load balancing algorithm can be fine-tuned to further optimize packet distribution and link performance.

[0134] The effect of the above technical solution is: by continuously collecting real-time status information of each link, including bandwidth utilization, delay, jitter, packet loss rate and link stability, the system can fully understand the current network status. The accuracy of real-time status information helps the system make more reasonable decisions, thereby optimizing the data transmission path and improving transmission efficiency. The link performance evaluation model constructed based on historical data and real-time data can comprehensively consider multiple performance indicators of the link and give a comprehensive performance score of the link. The model can accurately reflect the actual performance of the link and provide a reliable basis for data packet allocation. According to the performance evaluation results of the link, the distribution of data packets on multiple links is dynamically adjusted through the load balancing algorithm. When the performance of a link decreases, the system can automatically transfer the data packet to other links with better performance, thereby avoiding data transmission interruption or delay. After the data packet allocation is adjusted, the system continuously monitors the load and transmission performance of each link and establishes a feedback mechanism. The monitoring results are fed back to the load balancing algorithm in real time, and fine-tuning is performed according to the actual situation to ensure that the network always maintains the best state. By dynamically adjusting the distribution of data packets on multiple links, the system can ensure that resources are reasonably allocated. Links with better performance take on more data transmission tasks, while links with poorer performance reduce data transmission accordingly, thereby improving overall resource utilization. Optimized data transmission paths and resource allocation help reduce the energy consumption of network devices. By reducing unnecessary transmission overhead and delay, the system can reduce overall energy consumption and improve energy efficiency. Through mechanisms such as real-time status information collection, link performance evaluation models, and dynamic load balancing, the system can ensure stable data transmission. Users can enjoy a smoother and more stable data transmission experience, improving satisfaction and loyalty. The system has established a feedback mechanism to detect and solve potential transmission problems in a timely manner. In the event of a failure, the system can respond quickly and resume data transmission, reducing user waiting time and losses.

[0135] In one embodiment of the present invention, S3 includes:

[0136] S31, real-time monitoring of key indicators of each link, the key indicators including signal quality, bit error rate and packet loss rate; and improving the accuracy and real-time performance of monitoring through signal processing algorithms during the monitoring process;

[0137] S32. According to the monitoring results, dynamically adjust the transmission rate and power allocation of each link; when the performance of a link degrades, automatically reduce the load of the link or switch to a backup link;

[0138] S33, using a load balancing algorithm, evenly distribute the data packets to each link, and perform real-time evaluation on the resource utilization of each link. The resource utilization is evaluated using the following formula:

[0139]

[0140] Where RUIξ(f) represents the resource utilization of the ξth link at time f; F is the length of the time window for evaluating resource utilization; Cξ(τ) is the current transmission rate of the ξth link at time τ; Mξ is the maximum transmission capacity of the ξth link.

[0141] The working principle of the above technical solution is as follows: the system monitors the key indicators of each link in real time, including signal quality, bit error rate and packet loss rate. During the monitoring process, the system improves the accuracy and real-time performance of monitoring by applying signal processing algorithms (such as adaptive filtering and blind source separation). According to the real-time monitoring results, the system dynamically adjusts the transmission rate and power allocation of each link. When the link performance is good, the system can increase the transmission rate and power allocation to make full use of the link resources. When the link performance decreases, the system automatically reduces the load of the link, reduces the transmission rate and power allocation. When a link has a serious performance degradation, the system can automatically switch to a backup link, and the selection of the backup link is based on the real-time monitoring results and link performance evaluation. The system evenly distributes data packets to each link through a load balancing algorithm to balance the load of each link. The load balancing algorithm takes into account factors such as the real-time performance, transmission capacity and resource utilization of the link to ensure that the data packets can be transmitted efficiently and stably. The system evaluates the resource utilization of each link in real time, including bandwidth utilization, power utilization, etc. The evaluation results are used to guide the adjustment of transmission rate and power allocation, as well as the optimization of the load balancing algorithm. Through continuous evaluation and optimization, the system can ensure that the resources of each link are fully utilized while avoiding resource waste and performance bottlenecks.

[0142] The effect of the above technical solution is: by real-time monitoring of the key indicators of each link (signal quality, bit error rate, packet loss rate, etc.), the system can timely discover problems in the link and take corresponding optimization measures to ensure the stability and reliability of data transmission. The application of signal processing algorithms such as adaptive filtering and blind source separation can further improve the accuracy and real-time performance of monitoring. The adaptive filtering algorithm can dynamically adjust the parameters of the filter to better suppress noise and interference, thereby improving the accuracy of signal quality monitoring. The blind source separation algorithm can separate each source signal from the mixed signal, which helps to accurately evaluate the bit error rate and packet loss rate of the link. According to the monitoring results, the system can dynamically adjust the transmission rate and power allocation of each link. When the link performance is good, the system can increase the transmission rate and power allocation to make full use of the link resources. When the link performance decreases, the system automatically reduces the load of the link to reduce the bit error rate and packet loss rate and ensure the stability of data transmission. When a link has a serious performance degradation, the system can automatically switch to the backup link to ensure the continuity of data transmission. At the same time, through the load balancing algorithm, the system can evenly distribute data packets to each link, avoid overloading a single link, and improve the transmission efficiency and stability of the overall network. The system evaluates the resource utilization of each link in real time, including bandwidth utilization, power utilization, etc., can find resource waste and performance bottlenecks, and take corresponding optimization measures. By dynamically adjusting the transmission rate and power allocation, and applying the load balancing algorithm, the system can ensure that the resources of each link are fully utilized. Since the system can monitor the key indicators of the link in real time and take prompt measures when problems are found, it can respond quickly to link failures. Through continuous monitoring, evaluation and optimization, the system can continuously improve the performance of the link. This helps to ensure that the network is always in the best state and improve the stability of the network. The above resource utilization evaluation formula calculates the resource utilization in real time, and the system can make timely adjustments when the link load changes. If it is found that the utilization of a link is too high, the system can actively transfer part of the traffic to other links to avoid overloading a single link and causing performance degradation. Combined with the load balancing algorithm, this formula enables data packets to be more evenly distributed to each link, improving the transmission efficiency of the overall network, reducing congestion on a single link, and improving the user experience. By monitoring and calculating the resource utilization of each link, the network management system can evaluate the performance of the link in real time. This provides important data support for subsequent network optimization and fault detection, and can quickly identify links with degraded performance. By analyzing the link utilization, the management system can predict future changes in the load capacity of the link. This predictive ability can help network managers take measures in advance to prevent link overload and ensure the smooth operation of the network. Based on the calculation results of this formula, the network management system can provide a quantitative basis for decisions such as traffic scheduling and link selection. Data-driven decision-making makes network management more intelligent and more adaptable.The introduction and application of the above formula not only improves the accuracy and real-time performance of resource utilization evaluation of network links, but also provides an important theoretical basis and practical tools for network management and optimization, promoting the improvement of network performance and user experience.

[0143] In one embodiment of the present invention, the S4 includes:

[0144] S41, the receiving end reassembles the data packets from multiple physical links based on the order and integrity of the data packets according to the link identifier, timestamp and other information;

[0145] S42, verifying the reorganized data using a cyclic redundancy check algorithm to detect whether there is data loss or error;

[0146] S43, if a lost or erroneous data packet is detected, recovery is performed through a retransmission mechanism;

[0147] S44, and caches frequently requested data packets through an intelligent caching mechanism.

[0148] The working principle of the above technical solution is as follows: at the receiving end, the system first identifies and processes data packets from multiple physical links based on information such as link identifiers and timestamps; based on the order and integrity of these data packets, the system reassembles them; the reassembled data will be verified by a cyclic redundancy check (CRC) algorithm; by comparing the data check codes at the sending and receiving ends, the system can accurately identify whether the data has changed or lost during the transmission process; once data loss or error is detected, the system will trigger a retransmission mechanism; the retransmission mechanism can be implemented based on protocols such as automatic repeat request (ARQ). For example, according to the priority of the data packet and the real-time status of the link, the system will dynamically adjust the retransmission strategy. Prioritizing the retransmission of high-priority data packets can ensure the timely transmission of critical data; and retransmission on a link with better signal quality can improve the success rate and efficiency of retransmission; in order to further improve the efficiency and reliability of data transmission, the technical solution also introduces an intelligent cache mechanism; the system will cache frequently requested data packets. When the same data packet is requested again, the system can directly read the data from the cache without having to transmit it again from the physical link.

[0149] The effect of the above technical solution is that the receiving end can accurately reorganize the data packets from multiple physical links according to the information such as link identification and timestamp, ensure that the order and integrity of the data packets in the transmission process are restored, and provide a reliable basis for subsequent data processing. Through accurate data packet reorganization, the system can avoid duplication and loss of data packets in the transmission process, thereby improving the efficiency of data transmission, reducing network congestion and delay, and improving the performance of the overall network. The cyclic redundancy check algorithm is used to verify the reorganized data, which can reliably detect data loss or errors. Through data verification, the system can timely discover and correct data errors in the transmission process, thereby reducing the error rate of data transmission, improving the accuracy and reliability of data processing, and ensuring the correctness and consistency of data. The retransmission mechanism is based on protocols such as ARQ or HARQ, but has been innovatively improved. For example, according to the priority of the data packet and the real-time status of the link, the retransmission strategy is dynamically adjusted, and the optimal retransmission method can be selected according to the actual situation, which improves the efficiency of retransmission. By giving priority to retransmitting high-priority data packets, the system can ensure the timely transmission of key data, improve the response speed and stability of the system, especially when processing emergency tasks or key data. Retransmission on links with better signal quality can improve the success rate and efficiency of retransmission, optimize the utilization of link resources, and reduce unnecessary resource waste. Through the intelligent caching mechanism, the system can cache frequently requested data packets, reduce repeated data transmission, and improve the speed and efficiency of data transmission. The intelligent caching mechanism can reduce data transmission delays and bandwidth usage, thereby improving the user experience. Especially when processing a large number of data requests, the caching mechanism can significantly speed up the data response speed.

[0150] One embodiment of the present invention, as Figure 2 As shown, an MBB multi-path local aggregation overlay transmission system includes:

[0151] Link aggregation module: establishes multiple physical links in the wireless communication system. The system selects the best multiple physical links for aggregation based on the current network environment, device status and user needs;

[0152] Data transmission module: divides the data to be transmitted into multiple data packets, encapsulates each data packet according to the characteristics of the selected physical link, and transmits the encapsulated data packets in parallel through the selected physical link;

[0153] Status monitoring module: During the transmission process, the system monitors the transmission status of each link in real time, including signal quality, bit error rate, packet loss rate, etc., and dynamically adjusts the transmission rate and power allocation of each link according to the current network load and device status;

[0154] Data verification module: After the receiving end receives data packets from multiple physical links, it reassembles the data packets according to the link identifier and timestamp, and verifies the reassembled data to detect whether there is data loss or error; for lost or erroneous data, the system attempts to recover through a retransmission mechanism.

[0155] The working principle of the above technical solution is as follows: In a wireless communication system, multiple physical links are first established as channels for data transmission. The system selects the optimal multiple physical links for aggregation according to factors such as the current network environment (such as signal strength, interference), device status (such as transmission power, receiving sensitivity) and user needs (such as data transmission rate, reliability requirements), for example, the one with the strongest signal, the highest receiving sensitivity and the highest transmission rate. The data to be transmitted is divided into multiple data packets, each of which is encapsulated according to the characteristics of the selected physical link, including adding link identification, timestamp and other information. The encapsulated data packets are transmitted in parallel through the selected physical link, thereby making full use of the bandwidth resources of multiple links. During the transmission process, the system monitors the transmission status of each link in real time, including key indicators such as signal quality, bit error rate, and packet loss rate. According to the current network load and device status, the system dynamically adjusts the transmission rate and power allocation of each link. After receiving the data packets from multiple physical links, the receiving end reassembles the data packets according to the link identification and timestamp. The reassembled data is checked to detect whether there is data loss or error. For lost or erroneous data, the system attempts to recover through the retransmission mechanism to ensure the reliability of data transmission.

[0156] The effect of the above technical solution is: by establishing multiple physical links and aggregating them, parallel data transmission is realized. Compared with single link transmission, the data transmission rate and throughput can be significantly improved. The system can select the optimal multiple physical links for aggregation according to the current network environment, device status and user needs, ensuring that data transmission is always carried out on the best link, thereby improving transmission efficiency. During the transmission process, the system monitors the transmission status of each link in real time, including key indicators such as signal quality, bit error rate, and packet loss rate. According to these indicators, the system can dynamically adjust the transmission rate and power allocation of each link to ensure the stability and reliability of data transmission. After the receiving end receives data packets from multiple physical links, it reassembles the data packets according to the link identifier and timestamp. At the same time, the reassembled data is checked to detect whether there is data loss or error. For lost or erroneous data, the system attempts to recover through a retransmission mechanism, thereby further enhancing the reliability of data transmission. The system can dynamically adjust the transmission rate of each link according to the current network load and device status. The flexible adjustment mechanism can ensure that when the network load is high, the transmission rate is reduced to avoid network congestion; when the network load is low, the network resources are fully utilized by increasing the transmission rate. In addition to the transmission rate, the system can also dynamically adjust the power allocation of each link to ensure that the power of each link is reasonably allocated during the transmission process, thereby improving energy efficiency and reducing energy consumption. It can be dynamically adjusted according to user needs to meet the different needs of different users for data transmission rate, reliability and stability. The above technical solution can be widely used in various wireless communication scenarios, such as video conferencing, online games, high-definition video transmission, etc. By improving data transmission efficiency and reliability, the above technical solution can significantly improve the user's service quality experience. For example, in video conferencing, users can enjoy a smoother and clearer video call experience; in online games, users can enjoy lower latency and higher game stability.

[0157] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for MBB multi-path local aggregation overlay transmission, characterized in that: The method comprises: S1. Establish multiple physical links in the wireless communication system. The system selects the optimal multiple physical links for aggregation according to the current network environment, device status and user needs; S2, dividing the data to be transmitted into multiple data packets, encapsulating each data packet according to the characteristics of the selected physical link, and transmitting the encapsulated data packets in parallel through the selected physical link; S3. During the transmission process, the system monitors the transmission status of each link in real time and dynamically adjusts the transmission rate and power allocation of each link according to the current network load and device status; S4. After receiving the data packets from multiple physical links, the receiving end reassembles the data packets according to the link identifiers and timestamps, and verifies the reassembled data.

2. According to claim 1, a method for MBB multi-channel local aggregation overlay transmission is characterized in that: Said S1 comprises: S11, scanning available wireless spectrum resources to identify potential physical links; evaluating the signal quality of each potential link; and calculating the correlation between the links; S12, real-time monitoring of the status of the device, wherein the status of the device includes battery power, processing capacity, and heat dissipation status; S13, analyzing the current user needs of the user, wherein the user needs include data transmission rate, delay requirement, and data priority; S14. Based on the above results, multiple optimal physical links are selected for aggregation through a multi-objective optimization algorithm.

3. According to claim 1, a method for MBB multi-channel local aggregation overlay transmission is characterized in that: The S2 comprises: S21, dividing the data to be transmitted into multiple data packets according to the data size, assigning a priority to each data packet, and giving priority to transmitting the data packet with a high priority; S22. Add encapsulation information to each data packet according to the characteristics of the selected physical link, where the encapsulation information includes a link identifier, a check code, and a timestamp; S23, transmitting the encapsulated data packets in parallel through a multi-channel transmission protocol, and dynamically adjusting the transmission order and rate of the data packets according to the real-time status of each link during the transmission process.

4. According to claim 3, a method for MBB multi-channel local aggregation overlay transmission is characterized in that: The S22 comprises: S221. Collect detailed characteristics of all currently available physical links, where the detailed characteristics include bandwidth, delay, bit error rate, jitter rate, and stability; S222, based on the collected link characteristic data, the transmission efficiency of each link is evaluated by a multi-objective optimization algorithm, and a data packet allocation strategy is formulated accordingly; S223, based on the dynamic changes of the link, periodically monitor and evaluate the link status, and dynamically adjust the link selection strategy based on the evaluation results; S224, adding a link identifier to each data packet so that the data packet can be correctly routed to the target receiving end in a complex network environment; S225, generate and add a check code to verify the integrity of the data packet at the receiving end, and detect and correct errors that may occur during the transmission process; S226, embed timestamp information, record the time of data packet encapsulation, and assign different priority levels to the data packets according to the priority identifier of the data packets and the business logic or application requirements; S227, and based on the existing redundant coding scheme, dynamically adjust the redundancy according to the bit error rate of the link; S228. Predict the change trend of link performance in the future by using the link characteristic prediction model, and pre-adjust the encapsulation format and redundancy of the data packet based on the prediction result.

5. According to claim 4, a method for MBB multi-channel local aggregation overlay transmission is characterized in that: The S228 includes: Extract relevant indicators of each physical link from the historical database, wherein the relevant indicators include bandwidth utilization, delay variation, bit error rate history, jitter rate trend, and stability index; The most influential features for link performance prediction are selected through feature selection algorithms and normalized. Model training is performed based on time series analysis, and model parameters are adjusted through cross-validation. The current and recent link status data are used as input to the trained prediction model; The prediction model outputs relevant prediction values ​​of the link in the future period; the relevant prediction values ​​include bandwidth availability, delay variation range, expected bit error rate and jitter level; and calculates the uncertainty interval of the prediction result; Dynamically adjust the packet segment size based on predicted future bandwidth availability and latency, and enable additional error detection and correction mechanisms for links with high bit error rates; Based on the prediction of link performance, the routing path of the data packet is optimized, and the redundant coding level in the data packet is dynamically adjusted according to the predicted bit error rate; The optimal redundancy configuration is calculated through a redundancy optimization algorithm based on the link characteristic prediction results; Through the real-time feedback system, the redundancy strategy is adjusted according to the actual performance of data packet transmission; Based on the prediction results, the encapsulation format and redundancy are configured for the data packets to be transmitted. During the data transmission process, the actual link performance is continuously monitored and compared with the prediction results. If there is a deviation, the adaptive adjustment mechanism is immediately triggered to dynamically adjust the data packet encapsulation and redundancy settings.

6. According to claim 3, a method for MBB multi-path local aggregation overlay transmission is characterized in that: The S23 comprises: S231, configuring the parameters of the parallel transmission protocol, and determining the transmission order of the data packets on the multiple links according to the priority, link status and service requirements of the data packets through the data packet scheduling algorithm; S232, and transmit through a multi-channel transmission protocol, during the transmission process, monitor the load and signal quality of each link in real time, evaluate the real-time status of the link based on the real-time monitoring results; based on the evaluation results, dynamically adjust the transmission rate on each link; S233, dynamically adjusting the distribution of data packets on multiple links according to the real-time status and transmission requirements of the links through a load balancing algorithm; S234. In addition, during the transmission process, the integrity and transmission delay of the data packet are detected using the check code and the timestamp, and the detected erroneous or lost data packets are recovered using a preset error recovery strategy.

7. The MBB multi-path local aggregation overlay transmission method according to claim 6, characterized in that: The S232 includes: According to the network environment and business requirements, corresponding key parameter settings are performed, and multiple parallel transmission channels are initialized based on the configured parameters; Through the link status monitor deployed on each transmission channel, the key performance indicators of the link are collected in real time, including bandwidth utilization, delay and packet loss rate; Preprocess the collected raw data and aggregate the preprocessed data to a unified monitoring platform. Build a link status assessment model based on historical data and real-time data. Use the link status assessment model to assess the current status of the link and predict the change trend in the future. According to the actual business needs and network environment, set reasonable warning thresholds for various link performance indicators. If a certain indicator is detected to exceed the threshold, the warning mechanism is triggered immediately. According to the link status evaluation results, a transmission rate adjustment strategy is designed; based on the adjustment strategy, each channel is adjusted in real time.

8. The MBB multi-path local aggregation overlay transmission method according to claim 1, characterized in that: The S3 includes: S31, real-time monitoring of key indicators of each link, the key indicators including signal quality, bit error rate and packet loss rate; and improving the accuracy and real-time performance of monitoring through signal processing algorithms during the monitoring process; S32. According to the monitoring results, dynamically adjust the transmission rate and power allocation of each link; when the performance of a link degrades, automatically reduce the load of the link or switch to a backup link; S33. The data packets are evenly distributed to each link through the load balancing algorithm, and the resource utilization of each link is evaluated in real time.

9. The MBB multi-path local aggregation overlay transmission method according to claim 1, characterized in that: The S4 comprises: S41, the receiving end reassembles the data packets from multiple physical links according to the link identifier and the timestamp, based on the order and integrity of the data packets; S42, verifying the reorganized data using a cyclic redundancy check algorithm to detect whether there is data loss or error; S43, if a lost or erroneous data packet is detected, recovery is performed through a retransmission mechanism; S44, and caches frequently requested data packets through an intelligent caching mechanism.

10. An MBB multi-channel local aggregation overlay transmission system, characterized in that: The system comprises: Link aggregation module: establishes multiple physical links in the wireless communication system. The system selects the best multiple physical links for aggregation based on the current network environment, device status and user needs; Data transmission module: divides the data to be transmitted into multiple data packets, encapsulates each data packet according to the characteristics of the selected physical link, and transmits the encapsulated data packets in parallel through the selected physical link; Status monitoring module: During the transmission process, the system monitors the transmission status of each link in real time, and dynamically adjusts the transmission rate and power allocation of each link according to the current network load and device status; Data verification module: After receiving data packets from multiple physical links, the receiving end reassembles the data packets according to the link identifier and timestamp, and verifies the reassembled data.

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