Satellite communication transmission optimization method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a satellite communication transmission optimization method and device, electronic equipment and a storage medium, and relates to the technical field of satellite communication and data transmission optimizing.The method comprises the steps that a stream context table is inquired by extracting a data packet head quintuple, and a new stream is created and synchronously updated when the data packet head quintuple is not hit. An ROHC compressor is used for compressing the head of a data packet, a compressed data segment containing a CID is generated and stored in an FIFO queue, after the size or duration condition is met, the compressed data segment is packaged into an aggregation frame, and FEC coding is added for sending, so that the transmission redundancy is reduced, and the transmission efficiency is improved for a high-error-code long-delay environment. By dynamically increasing the number of IR packet sending times, the state of a compressor is adaptively adjusted, light NACK is sent, and a flow context table is periodically cleaned. And dividing priorities according to service types, configuring differentiated aggregation parameters, reading TCP layer state information in real time for dynamic adjustment, and marking an NACK packet as the highest priority. According to the invention, the problems of efficiency bottleneck and poor transmission robustness in the prior art are effectively solved.

Description

A satellite communication transmission optimization method, apparatus, electronic device, and storage medium Technical Field

[0001] This invention relates to the field of satellite communication and data transmission optimization technology, and in particular to a satellite communication transmission optimization method, apparatus, electronic device and storage medium. Background Technology

[0002] With the rapid development of satellite internet, high-orbit satellites, as core nodes for wide-area coverage, face three major challenges in their communication links: ultra-high transmission latency, high link error rate, and limited bandwidth resources. These inherent characteristics have caused severe bottlenecks in the application of traditional TCP protocols in high-orbit satellite environments.

[0003] Traditional TCP protocol header overhead accounts for too high a proportion, especially when transmitting small data packets, where ineffective overhead severely squeezes the space for effective data transmission. At the same time, high latency amplifies retransmission loss, and the loss of a single data packet can block the entire transmission window for hundreds of milliseconds. In addition, the high error rate exacerbates header redundancy loss, and frequent retransmissions lead to the repeated sending of the complete TCP header, further wasting scarce bandwidth resources.

[0004] However, existing single optimization techniques, such as relying solely on header compression or packet aggregation, cannot simultaneously solve the above problems. While header compression can reduce the overhead of a single packet header, it generates more micro-packets, increasing the number of transmissions and the probability of packet loss; packet aggregation only reduces the number of transmissions without optimizing the problem of duplicate transmission of the TCP header itself.

[0005] Therefore, there is an urgent need for a satellite communication transmission optimization method that can overcome the bottleneck of transmission efficiency, adapt to the multi-service converged transmission scenario of high-orbit satellites, and improve the efficiency and stability of satellite communication. Summary of the Invention

[0006] The embodiments of the present invention provide a satellite communication transmission optimization method to solve the problems of large header overhead, poor adaptability to high latency and high bit error rate, slow single header compression synchronization, lack of differentiated design, and difficulty in balancing latency and efficiency in the prior art. The technical solution is as follows: According to one aspect of the present invention, a satellite communication transmission optimization method includes: acquiring data packets; extracting the header 5-tuple of the data packets and querying a flow context table; if the query matches the 5-tuple, associating the data packets with the matched flow context; otherwise, creating a new flow context and synchronously updating the data; compressing the header of the data packets to generate compressed data segments and storing them in a FIFO queue; when the size or duration of the FIFO queue meets the set requirements, encapsulating the data segments in the FIFO queue into an aggregate frame, adding FEC encoding, and sending it to the link layer; optimizing transmission by increasing the number of IR packet transmissions when the bit error rate exceeds a set threshold, dynamically adjusting the compressor state according to the quality of the transmission link, sending a lightweight NACK when a minor anomaly occurs, and periodically cleaning the flow context table; the minor anomaly includes packet loss and decompression failure; prioritizing according to service type and configuring aggregation parameters for different priorities, reading TCP layer status information in real time and dynamically adjusting aggregation parameters, and automatically marking the NACK packet as the highest priority; the aggregation parameters include a timeout threshold and a size threshold.

[0007] In one embodiment, the process involves extracting the header 5-tuple of the data packet and querying the flow context table. If the query matches the 5-tuple, the data packet is associated with the matched flow context; otherwise, a new flow context is created and the data is updated synchronously. This is achieved through the following steps: extracting the IP / TCP header 5-tuple of the data packet, querying the 5-tuple in the flow context table, and if it already exists, directly associating the data packet with the corresponding flow context; if it does not exist, creating a new flow context in the flow context table based on the 5-tuple, updating the 5-tuple in the flow context table, and synchronously updating the status information of the flow context table.

[0008] In one embodiment, the header of the data packet is compressed to generate a compressed data segment and stored in a FIFO queue. When the size or duration of the FIFO queue meets the set requirements, the data segments in the FIFO queue are encapsulated into an aggregate frame through the following steps: the ROHC compressor retrieves the context data of the flow context corresponding to the data packet from the flow context table, compresses the header of the data packet according to the context data, and generates a compressed data segment containing a context identifier (CID); the compressed data segment is stored in the FIFO queue of the flow context corresponding to the data packet, and the size and duration of the queue are monitored. If the size reaches a set size threshold or the duration reaches a set timeout threshold, all data segments in the FIFO queue are encapsulated into an aggregate frame containing a sequence number and the number of data segments.

[0009] In one embodiment, increasing the number of IR packet transmissions when the bit error rate exceeds a set threshold is achieved through the following steps: real-time monitoring of the bit error rate of the transmission link and comparing it with a preset threshold; if the bit error rate exceeds the threshold, increasing the number of IR packet transmissions; the increase in the number of IR packet transmissions is used to ensure that the receiving end can quickly capture context information.

[0010] In one embodiment, dynamically adjusting the compressor state based on the quality of the transmission link, sending a lightweight NACK when a minor anomaly occurs, and periodically cleaning the flow context table are achieved through the following steps: monitoring link anomaly signals transmitted by the TCP layer in the transmission link to predict link deterioration trends; the anomaly signals include ACK confirmation timeouts and increased packet retransmission counts; when the link deterioration trend exceeds a set condition, the compressor state is downgraded, and more context information is sent for resynchronization; when decompression failure or frame corruption occurs, a lightweight NACK containing only a frame corruption identifier is sent to the sending end, the compressor state is downgraded, and resynchronization is performed.

[0011] In one embodiment, prioritizing services based on service type and configuring aggregation parameters for different priorities is achieved through the following steps: services are divided into highest priority, second-highest priority, and lowest priority based on service information; the service information includes a 5-tuple, a DSCP tag, and a port number; a minimum timeout threshold and a minimum size threshold are configured for the highest priority service; a maximum timeout threshold and a maximum size threshold are configured for the lowest priority service; strict priority scheduling is applied to the highest priority queue, and weighted fair queue scheduling is applied to the second-highest and lowest priority queues according to set weights; the weights are dynamically adjusted based on the service type.

[0012] In one embodiment, real-time reading of TCP layer status information and dynamic adjustment of aggregation parameters, automatically marking the NACK packet as the highest priority, is achieved through the following steps: real-time reading of TCP layer status information to detect whether a link deterioration signal occurs; the status information includes ACK timeout count, retransmission counter, and congestion window changes; when link deterioration is detected, dynamic adjustment of aggregation parameters is triggered; the dynamic adjustment of aggregation parameters includes increasing queue priority and shortening timeout threshold; the generated NACK packet is automatically marked as the highest priority; the NACK packet includes decompression failure information and frame corruption information. According to one aspect of the present invention, a satellite communication transmission optimization device includes: a flow context association module, used to acquire data packets, extract the header 5-tuple of the data packet and query the flow context table; if the query matches the 5-tuple, the data packet is associated with the matched flow context; otherwise, a new flow context is created and the data is updated synchronously; a header compression aggregation module, used to compress the header of the data packet to generate compressed data segments and store them in a FIFO queue; when the size or duration of the FIFO queue meets set requirements, the data segments in the FIFO queue are encapsulated into an aggregate frame and FEC encoding is added. The code is then sent to the link layer; the transmission fault tolerance optimization module is used to optimize transmission by increasing the number of IR packet transmissions when the bit error rate exceeds a set threshold, dynamically adjusting the compressor state according to the quality of the transmission link, sending a lightweight NACK when a minor anomaly occurs, and periodically cleaning the flow context table; the minor anomaly includes packet loss and decompression failure; the multi-service dynamic scheduling module is used to divide priorities according to service type and configure aggregation parameters for different priorities, read TCP layer status information in real time and dynamically adjust aggregation parameters, and automatically mark the NACK packet as the highest priority; the aggregation parameters include timeout threshold and size threshold.

[0013] According to one aspect of the present invention, an electronic device includes at least one processor and at least one memory, wherein computer-readable instructions are stored in the memory; the computer-readable instructions are executed by one or more of the processors to cause the electronic device to implement the satellite communication transmission optimization method as described above.

[0014] According to one aspect of the present invention, a storage medium storing computer-readable instructions that are executed by one or more processors to implement the satellite communication transmission optimization method as described above.

[0015] The beneficial effects of the technical solution provided by this invention are as follows: Firstly, by extracting the five-tuple from the packet header and querying the flow context table, this invention achieves accurate association between packets and flow contexts. If a match is not found, a new flow is created and updated synchronously. The packet header is compressed using the ROHC compressor to generate compressed data segments containing CIDs, which are then stored in a FIFO queue. After meeting size or duration conditions, these segments are encapsulated into aggregate frames and FEC encoding is added before transmission to reduce transmission redundancy. For high-error-rate, long-latency environments, transmission robustness is enhanced by dynamically increasing the number of IR packet transmissions, adaptively adjusting the compressor state, sending lightweight NACK packets, and periodically cleaning the flow context table. Simultaneously, priorities are assigned based on service type, differentiated aggregation parameters are configured, and TCP layer status information is read in real-time for dynamic adjustment. NACK packets are marked as the highest priority to achieve QoS guarantees for multiple services. This method effectively solves the efficiency bottleneck of traditional TCP protocols and single optimization techniques in high-orbit satellite communication, significantly improving bandwidth utilization and transmission stability. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without creative effort.

[0017] Figure 1 is a flowchart illustrating a satellite communication transmission optimization method according to an exemplary embodiment; Figure 2 is a flowchart illustrating the transmitting end in the satellite communication transmission optimization method according to an exemplary embodiment; Figure 3 is a flowchart illustrating the receiving end in the satellite communication transmission optimization method according to the embodiment corresponding to Figure 2; Figure 4 is a schematic diagram of a system architecture using the satellite communication transmission optimization method in an application scenario; Figure 5 is a block diagram illustrating a satellite communication transmission optimization device according to an exemplary embodiment; Figure 6 is a hardware structure diagram illustrating an electronic device according to an exemplary embodiment; Figure 7 is a block diagram illustrating an electronic device according to an exemplary embodiment. Detailed Implementation

[0018] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0019] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this disclosure means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0020] This invention provides a satellite communication transmission optimization method. Through deep collaborative TCP header compression and packet aggregation technology, it significantly improves bandwidth utilization and transmission stability in high-orbit satellite communication, solving the efficiency bottlenecks and poor transmission robustness problems faced by traditional TCP protocols and single optimization techniques. This satellite communication transmission optimization method is applicable to satellite communication transmission optimization devices, which can be electronic devices. The satellite communication transmission optimization method in this invention can be applied to various scenarios, such as satellite communication transmission optimization.

[0021] Please refer to Figure 1. This embodiment of the invention provides a satellite communication transmission optimization method, which is applicable to electronic devices.

[0022] In the following method embodiments, for ease of description, the execution subject of each step of the method is an electronic device, but this does not constitute a specific limitation.

[0023] As shown in Figure 1, the method may include the following steps: Step 110, obtain the data packet, extract the header 5-tuple of the data packet and query the flow context table. If the query matches the 5-tuple, associate the data packet with the matched flow context; otherwise, create a new flow context and update the data synchronously.

[0024] In one possible implementation, the 5-tuple of the IP / TCP header of the data packet is extracted, and the 5-tuple is queried in the flow context table. If it already exists, the data packet is directly associated with the corresponding flow context; if it does not exist, a new flow context is created in the flow context table based on the 5-tuple, the 5-tuple is updated in the flow context table, and the state information of the flow context table is updated synchronously.

[0025] Specifically, the five-tuple information (source IP address, destination IP address, source port number, destination port number, and protocol type) of the IP / TCP header is extracted from the received data packet. Based on the extracted five-tuple information, the flow context table is checked to see if a corresponding flow context exists. If the query finds a match, the data packet is directly associated with the corresponding flow context; if not, a new flow context is created in the flow context table, and the status information in the table is updated.

[0026] Specifically, a data stream is uniquely identified using a 5-tuple, enabling precise association between data packets and the stream context, thus providing a foundation for subsequent processing. This avoids the resource waste caused by repeatedly creating stream contexts and improves processing efficiency. Simultaneously, the updated state information in the stream context table ensures the real-time nature and accuracy of the data.

[0027] In the above process, the embodiments of the present invention achieve accurate association between data packets and flow context by extracting the five-tuple of the data packet header and querying the flow context table, thereby avoiding resource waste, providing an efficient data flow management foundation, and realizing the real-time performance and accuracy of data processing.

[0028] Step 120: Compress the header of the data packet to generate a compressed data segment and store it in a FIFO queue. When the size or duration of the FIFO queue meets the set requirements, encapsulate the data segment in the FIFO queue into an aggregate frame, add FEC encoding, and send it to the link layer.

[0029] In one possible implementation, the ROHC compressor retrieves the context data corresponding to the data packet based on the internal flow context table. It then compresses the packet header according to the context data, generating a compressed data segment containing a context identifier (CID). This compressed data segment is stored in the FIFO queue of the corresponding flow context, and the queue size and duration are monitored. If the size reaches a set threshold or the duration reaches a set timeout threshold, all data segments in the FIFO queue are encapsulated into an aggregate frame containing a sequence number and the number of data segments. Specifically, the ROHC compressor retrieves the corresponding context data from the flow context table, compresses the data packet header, and generates a compressed data segment containing a context identifier (CID). This compressed data segment is stored in the corresponding flow's FIFO queue, and the queue size and duration are monitored. When the queue size reaches a set threshold or the duration reaches a set timeout threshold, all data segments in the queue are encapsulated into an aggregate frame containing a sequence number and the number of data segments, FEC encoding is added, and the frame is sent to the link layer.

[0030] The IR packet (Initialization and Refresh packet) is a control packet used for ROHC context initialization and refresh, containing complete flow context information; lightweight anomalies refer to situations where the severity of the anomaly is lower than a preset threshold, including packet loss rate higher than the set value and decompression failure rate higher than the set value.

[0031] Furthermore, header compression reduces single-packet overhead, and frame aggregation reduces the number of transmissions, thereby reducing bandwidth waste. The ROHC compressor effectively reduces unnecessary overhead in the packet header, while FIFO queues and frame aggregation mechanisms reduce the number of transmissions and improve bandwidth utilization. FEC encoding enhances the reliability of data transmission.

[0032] In the above process, the embodiments of the present invention compress the packet header using the ROHC compressor and store it in a FIFO queue for monitoring and aggregation frame encapsulation, which effectively reduces bandwidth waste, provides an efficient data transmission method, and achieves a significant improvement in bandwidth utilization.

[0033] Step 130 involves optimizing transmission by increasing the number of IR packet transmissions when the bit error rate exceeds a set threshold, dynamically adjusting the compressor state based on the quality of the transmission link, sending a lightweight NACK when a minor anomaly occurs, and periodically cleaning the flow context table.

[0034] In one possible implementation, the bit error rate of the transmission link is monitored in real time and compared with a preset threshold. If the bit error rate exceeds the threshold, the number of IR packet transmissions is increased, and link anomaly signals transmitted by the TCP layer in the transmission link are listened for to predict the link deterioration trend. When the link deterioration trend exceeds the set conditions, the state of the compressor is downgraded and more context information is sent for resynchronization. When decompression failure or frame corruption occurs, a lightweight NACK containing only a frame corruption identifier is sent to the sender, the state of the compressor is downgraded, and resynchronization is performed.

[0035] Increasing the number of IR packet transmissions is used to ensure that the receiver can quickly capture context information; abnormal signals include ACK confirmation timeout, increased number of data packet retransmissions, etc., and minor anomalies include packet loss and decompression failure, etc., none of which are specified here.

[0036] Specifically, the bit error rate of the transmission link is monitored in real time. When the bit error rate exceeds a set threshold, the number of IR packets (initialization and refresh packets) sent is increased to ensure that the receiver quickly captures context information. Link anomaly signals transmitted by the TCP layer (such as ACK acknowledgment timeouts and increased packet retransmissions) are listened for to predict link deterioration trends and dynamically adjust the compressor state. When decompression failure or frame corruption occurs, a lightweight NACK containing only a frame corruption flag is sent to the sender, and invalid flow context tables are cleaned up.

[0037] Specifically, to address the characteristics of satellite links with high bit error rates and long latency, transmission stability and robustness are improved by optimizing the transmission link and fault-tolerance mechanisms. Increasing the number of IR packet transmissions and dynamically adjusting the compressor state ensures rapid synchronization of context information and optimized compression efficiency. Lightweight NACK and stream context table cleanup mechanisms reduce reverse bandwidth waste and memory consumption, improving the long-term stability of the system.

[0038] In the above process, the embodiments of the present invention effectively optimize the transmission link by monitoring the bit error rate, dynamically adjusting the compressor state, sending lightweight NACKs, and cleaning the flow context table, providing a stable transmission environment and achieving a significant improvement in transmission robustness.

[0039] Step 140: Prioritize according to business type and configure aggregation parameters for different priorities. Read TCP layer status information in real time and dynamically adjust aggregation parameters to automatically mark NACK packets as the highest priority.

[0040] In one possible implementation, services are divided into highest priority, second highest priority, and lowest priority based on service information; the shortest timeout threshold and minimum size threshold are configured for the highest priority services; the longest timeout threshold and maximum size threshold are configured for the lowest priority services; strict priority scheduling is used for the highest priority queues, and weighted fair queue scheduling is used for the second highest priority and lowest priority queues.

[0041] The weighted fair queue scheduling uses a weight ratio of 2:1, which can be set according to the actual application scenario. Business information includes 5-tuples, DSCP tags, and port numbers, etc., while aggregation parameters include timeout thresholds, size thresholds, etc., none of which are specified here.

[0042] In one possible implementation, the TCP layer status information is read in real time to detect whether a link deterioration signal has occurred. When link deterioration is detected, the aggregation parameters are dynamically adjusted. The generated NACK packets are automatically marked as the highest priority and the corresponding size threshold is set to 0.

[0043] The status information includes ACK timeout count, retransmission counter, congestion window changes, etc. The dynamic adjustment of aggregation parameters includes increasing queue priority, shortening timeout threshold, etc. The NACK packet includes decompression failure information and frame corruption information, etc., none of which are specified here.

[0044] Specifically, services are categorized into highest, second-highest, and lowest priorities based on service information (such as 5-tuples, DSCP tags, and port numbers). Different timeout and size thresholds are configured for services of different priorities: the highest priority service is configured with the shortest timeout and minimum size thresholds, while the lowest priority service is configured with the longest timeout and maximum size thresholds. Real-time reading of TCP layer status information (such as ACK timeout counts, retransmission counters, and congestion window changes) detects link deterioration signals and dynamically adjusts aggregation parameters. Simultaneously, NACK packets are automatically marked as the highest priority.

[0045] Specifically, to address the differentiated transmission needs of multiple satellite services, service priority allocation and dynamic parameter adjustment are used to achieve QoS guarantees for multiple services and a dynamic balance between transmission efficiency and latency. Differentiated aggregation parameter configuration and real-time dynamic adjustment mechanisms ensure that different services obtain appropriate transmission resources according to their characteristics, improving overall transmission efficiency and user satisfaction. The highest priority marking of NACK packets ensures timely processing of feedback information, further enhancing the system's fault tolerance.

[0046] In the above process, the embodiments of the present invention effectively achieve QoS guarantee for multiple services and dynamic balance between transmission efficiency and latency by dividing service priorities, configuring differentiated aggregation parameters, reading TCP layer status information in real time and making dynamic adjustments, providing personalized transmission services and meeting the diverse needs in complex transmission scenarios.

[0047] Through the above process, this invention significantly improves bandwidth utilization and transmission stability in high-orbit satellite communication by implementing packet association and flow context management, packet header compression and aggregation frame encapsulation, transmission link optimization and fault tolerance processing, service priority allocation and dynamic parameter adjustment. It effectively solves the efficiency bottlenecks and poor transmission robustness issues faced by traditional TCP protocols and single optimization techniques, providing a highly efficient, stable, and customized transmission solution for satellite communication.

[0048] In an exemplary embodiment, data transmission using the satellite communication transmission optimization method of the present invention may include the following steps: As shown in FIG2, the transmitting end specifically includes the following steps: Step S1, extracting the quintuple.

[0049] Specifically, when a data packet enters the sending system, the flow classifier first processes the packet. It precisely extracts the five-tuple information from the IP / TCP header of the packet. This five-tuple includes the source IP address, destination IP address, source port number, destination port number, and protocol type. This step is fundamental to all subsequent processing; the five-tuple uniquely identifies a data flow, providing crucial information for subsequent flow context management.

[0050] In the above process, the embodiments of the present invention accurately identify data streams for targeted processing, ensuring that different data streams can be reasonably allocated and managed, thereby improving the system's ability to process different business data.

[0051] Step S2: Query the flow context.

[0052] Specifically, after extracting the quintuple, the stream classifier queries the stream context table. The stream context table stores relevant information for each data stream. If a stream context matching the extracted quintuple is found, the data packet is associated with the corresponding stream context; if no match is found, a new stream context is created in the stream context table, and the quintuple information is updated in the table, while the state information of the stream context table is updated synchronously.

[0053] In the above process, the embodiments of the present invention achieve effective tracking and management of data streams, ensuring that data packets can be processed in accordance with their respective data streams, improving the coherence and accuracy of data processing, and avoiding data chaos.

[0054] Step S3: Determine whether an existing flow is hit.

[0055] Specifically, this is the step of judging the query flow context results. If the query matches an existing flow, it means that the data flow to which the packet belongs has already been processed in the system, and the corresponding flow context information is available; if it does not match, it means that this is a new data flow, and a new flow context needs to be created. Different processing strategies are adopted according to whether the data flow already exists, so as to make reasonable use of system resources and improve processing efficiency.

[0056] Step S4: ROHC compresses the data packet to generate a CID compressed data segment.

[0057] Specifically, the ROHC compressor retrieves the context data from the flow context table corresponding to the data packet. Using this context data, the ROHC compressor compresses the packet header, generating a compressed data segment containing a context identifier (CID). The CID is used at the receiving end to identify the corresponding flow context for correct decompression.

[0058] In the above process, this embodiment of the invention effectively reduces redundant information in the data packet header, lowers data transmission volume, and saves bandwidth resources through ROHC compression technology. The introduction of CID ensures that the receiving end can accurately restore the original header information of the data packet.

[0059] Step S5: Receive the compressed data segment (store the compressed data segment into the FIFO queue). Specifically, the aggregation queue manager stores the compressed data segment generated by the ROHC compressor into the FIFO queue of the corresponding stream. During the storage process, the queue size and duration are monitored in real time, i.e., the two conditions: Threshold_S (size threshold) and Timer_T (timeout threshold).

[0060] In the above process, the embodiments of the present invention provide an orderly mechanism for the storage and subsequent processing of data segments through FIFO queues, while monitoring size and duration thresholds provide triggering conditions for the aggregation of data segments, ensuring that data can be aggregated and transmitted according to certain rules, thereby improving transmission efficiency.

[0061] Step S6: Determine the size Threshold_S or duration Timer_T, encapsulate the aggregate frame, and submit it to the link layer. That is, when the size or duration of the FIFO queue meets the set requirements, the data segments in the FIFO queue are encapsulated into an aggregate frame, FEC encoding is added, and then it is sent to the link layer.

[0062] Specifically, when the size of the FIFO queue reaches a set size threshold or the duration reaches a set timeout threshold, the aggregate frame constructor retrieves all data segments from the queue and encapsulates them into an aggregate frame containing a sequence number and the number of data segments. Then, FEC encoding is added to the aggregate frame, and finally, the encapsulated aggregate frame is sent to the link layer for transmission.

[0063] In the above process, the embodiments of the present invention reduce the number of data packet transmissions by encapsulating aggregated frames, further saving bandwidth resources. The addition of FEC encoding enhances the error resistance of data during transmission and improves the reliability of data transmission.

[0064] As shown in Figure 3, the receiving end specifically includes the following steps: Step S01, receiving data frames.

[0065] Specifically, after the receiving end's link layer completes FEC decoding, it hands the data frame over to the aggregate frame parser. This is the first step in the receiving end's data processing; it receives data frames from the link layer to prepare for subsequent parsing and processing. This ensures that the receiving end can obtain the data transmitted from the sending end, providing a foundation for subsequent data reconstruction and processing.

[0066] Step S02: Determine whether it is an aggregated frame.

[0067] Specifically, the aggregation frame parser identifies the frame type using the magic number. The magic number is a specific identifier used to determine whether a received data frame is an aggregation frame. If the data frame is not an aggregation frame, it is processed according to the normal packet processing procedure; if it is an aggregation frame, it proceeds to the subsequent parsing process.

[0068] In the above process, the embodiments of the present invention adopt different processing methods according to the type of data frame, thereby improving the efficiency and accuracy of data processing at the receiving end and ensuring that the data can be correctly restored and processed.

[0069] Step S03: Parse the packet header and obtain the list of data segments.

[0070] Specifically, once the received data frame is determined to be an aggregate frame, the aggregate frame parser first parses the header of the aggregate frame. The header contains key information such as the sequence number and the number of data segments. By parsing this information, the list of data segments in the aggregate frame can be accurately obtained, clarifying the number of data segments and their approximate storage structure within the aggregate frame, thus laying the groundwork for subsequent precise segmentation of the data.

[0071] In the above process, the embodiments of the present invention understand the overall structure of the aggregate frame and the basic information of the data segments, so that the subsequent data segmentation operation can be carried out more accurately and orderly, avoiding data segmentation errors and ensuring data integrity.

[0072] Step S04: Cut the data segment and parse the CID.

[0073] Specifically, based on the data segment list information obtained from the parsed packet header, the payload of the aggregated frame is precisely divided into N independent compressed data segments. After the data segmentation is completed, the CID (Context Identifier) ​​in the compression header of each segment is further parsed. The CID is a key identifier added by the sender when compressing the data segment. By parsing the CID, the receiver can determine the data stream to which each data segment belongs, so as to call the corresponding ROHC decompression engine for subsequent decompression operations.

[0074] In the above process, the embodiments of the present invention decompose the aggregated frame into independent data segments, and accurately identify the data stream to which the data segment belongs by parsing the CID, providing a key basis for the correct decompression of each subsequent data segment, and ensuring that the data can be accurately restored according to the data stream to which it belongs.

[0075] Step S05: Restore the TCP / IP header.

[0076] Specifically, each segment of compressed data is delivered to the corresponding ROHC decompression engine based on the CID in the compression header. The ROHC decompression engine uses the CID to access the corresponding stream context information, decompresses the compressed data segment, and reconstructs the complete TCP / IP header. This restores the compressed data segment to its original data format, recovering the complete header information of the data packet, enabling the packet to be correctly transmitted and processed in the network.

[0077] Step S06: Submit the IP protocol stack.

[0078] Specifically, the standard IP data packet, after recovering the TCP / IP header, is submitted to the host's IP protocol stack. The IP protocol stack, based on information such as the destination address of the data packet, forwards it to the appropriate application, completing the final delivery of the data. This enables the transmission of data from the transport layer to the application layer, ensuring that the data is correctly received and processed at the receiving end, thus completing the entire communication process.

[0079] Through the above process, this invention addresses the problems in satellite communication such as excessive protocol header overhead, redundant transmission times, poor robustness under high error / long latency, inability to balance QoS requirements of multiple services, and insufficient collaboration of single technologies. It proposes a complete satellite communication transmission optimization method. At the transmitting end, by extracting the five-tuple, managing the flow context, applying ROHC compression, monitoring the FIFO queue, and encapsulating aggregated frames, bandwidth waste is reduced from both single-packet cost and transmission frequency dimensions, with corresponding optimizations to compression efficiency and aggregation strategies. At the receiving end, by receiving data frames, determining frame type, parsing CID, segmenting data, restoring the TCP / IP header, and submitting the IP protocol stack, the data transmitted by the transmitting end is accurately restored. Simultaneously, through a fast context synchronization mechanism, adaptive state transition and fault-tolerant coding, lightweight exception handling and resource management mechanisms, and a multi-priority hybrid triggering aggregation strategy, the transmission stability problem under high error / long latency and the problem of differentiated transmission for multiple services are effectively solved. Furthermore, the constructed feedback-driven cross-layer collaborative mechanism breaks down the independent boundaries between compression and aggregation technologies, forming an optimization closed loop and further improving the overall system performance. This method has significant application value in scenarios such as satellite communication where data transmission efficiency and reliability are highly demanding.

[0080] In one application scenario, a data transmission optimization system was constructed using the satellite communication transmission optimization method proposed in this invention, and the system was used to optimize satellite communication transmission.

[0081] As shown in Figure 4, this data transmission optimization system consists of multiple modules, including a stream classifier, a ROHC compressor engine, an aggregation queue manager, an aggregation frame constructor, a satellite link, an aggregation frame parser, a ROHC decompressor engine, and a feedback processor. Specifically: The stream classifier classifies the input data stream. It first parses the header information of the data packets, and then maps and associates them with information in the stream context table based on the five-tuple (source IP address, destination IP address, source port number, destination port number, and protocol type). If the data stream to which the data packet belongs already exists, it is associated with the corresponding stream context; if it is a new data stream, a new entry is created in the stream context table and the relevant information is updated. It processes the header information of the data packets in the data stream, manages the stream context table through parsing and mapping operations, and provides the data stream's status and context information for subsequent compression processing.

[0082] The ROHC compressor engine specifically utilizes ROHC (Robust Header Compression) technology to compress the TCP / IP header of data packets. Based on context information in the flow context table, it efficiently compresses the packet header, generating compressed data segments containing the context identifier (CID). Simultaneously, it handles ROHC context synchronization information to ensure context consistency between the sender and receiver. It processes the TCP / IP header information and context information in the flow context table, outputting the compressed data segments and related context synchronization information.

[0083] Aggregation Queue Manager: Specifically, it maintains queues and manages aggregation logic. It stores compressed data segments output by the ROHC compressor engine into the corresponding stream's FIFO (First In First Out) queue and monitors the queue size and duration in real time. When the queue size reaches a set threshold or the duration reaches a set timeout threshold, the aggregation frame constructor is triggered to perform data aggregation operations. It processes compressed data segments and queue size and duration information, providing triggering conditions and data storage management for data aggregation by monitoring and managing queues.

[0084] Aggregate Frame Constructor: Specifically, when the aggregation queue manager triggers an aggregation operation, it retrieves all data segments from the corresponding queue and encapsulates them into an aggregate frame containing a sequence number and the number of data segments. Then, the aggregate frame is submitted to the satellite link for transmission, while simultaneously feeding back relevant aggregation information to the feedback processor. It processes compressed data segments, outputs the aggregate frame, and provides aggregation-related information to the feedback processor for subsequent processing and optimization.

[0085] Satellite link: As a data transmission channel, it transmits aggregated frames from the sending end to the receiving end.

[0086] Aggregate Frame Parser: Specifically, at the receiving end, it identifies and disassembles aggregate frames transmitted via satellite link. It first determines whether the received data is an aggregate frame; if so, it further parses the structure of the aggregate frame to obtain information such as the list of data segments. It processes the received aggregate frames and outputs the disassembled data segment list and other information, providing a foundation for subsequent data decompression and recovery.

[0087] The ROHC decompressor engine: Specifically, based on the CID in the data segment, it calls the corresponding stream context information to decompress the compressed data segment, reconstruct the complete TCP / IP header, and restore the original data format. Simultaneously, it processes ROHC context synchronization information to ensure that the context of the receiving and sending ends remains consistent. After processing the compressed data segment and context synchronization information, it outputs the decompressed packet header information, enabling the data to be restored to its original state.

[0088] Feedback processor: Specifically, it receives feedback information from the aggregate frame constructor and other modules, such as the transmission status of aggregate frames and context synchronization status. Based on this feedback information, it monitors and adjusts the overall system operation, such as adjusting the compressor status and aggregation parameters to optimize system performance. It processes various feedback information during system operation, achieving dynamic optimization and adjustment of the system through feedback processing.

[0089] As shown in Figure 4, this system optimizes data transmission. The ground station acts as the sender, and the data stream first enters the stream classifier. The stream classifier parses the header information of the data packets and maps them to the stream context table based on the five-tuple. For example, for a new video stream data packet, since its corresponding data stream does not exist in the stream context table, the stream classifier creates a new stream context entry and updates the relevant information; while for existing file transfer data stream packets, they are directly associated with the corresponding stream context.

[0090] Furthermore, the ROHC compressor engine compresses the TCP / IP header of data packets based on the context information in the stream context table. Taking video stream data packets as an example, after ROHC compression, a compressed data segment containing the CID is generated, reducing the redundancy of header information.

[0091] Furthermore, the aggregation queue manager stores the compressed data segments into the corresponding stream's FIFO queue and monitors the queue size and duration in real time. Assuming the video stream data volume is large, the queue size quickly reaches the set threshold, triggering the aggregation frame constructor.

[0092] Furthermore, the aggregate frame constructor extracts all compressed data segments from the queue, encapsulates them into aggregate frames containing sequence numbers and the number of data segments, submits them to the satellite link for transmission, and feeds back the aggregation-related information to the feedback processor.

[0093] Furthermore, the aggregated frames are transmitted via satellite link. Due to the high error rate of satellite links, this may affect the data in the aggregated frames; however, the system ensures data integrity through subsequent decompression and error correction mechanisms.

[0094] Furthermore, the server on the satellite acts as the receiving end, and the aggregated frame first reaches the aggregated frame parser. The aggregated frame parser identifies and breaks down the aggregated frame to obtain a list of data segments within it. For example, for a received video stream aggregated frame, it parses out the multiple video data segments it contains.

[0095] Furthermore, the ROHC decompressor engine uses the CID in the data segment to call the corresponding stream context information, performs decompression operations on the compressed data segment, reconstructs the complete TCP / IP header, and restores the original format of the video data.

[0096] Furthermore, the feedback processor receives feedback information from various modules, such as the context synchronization status during decompression. If a context desynchronization is detected, the feedback processor notifies the ROHC decompressor engine and the ROHC compressor engine at the sending end to make adjustments to ensure correct data decompression. Simultaneously, based on feedback information such as the transmission status of aggregated frames, the processor dynamically optimizes the operating parameters of the entire system to improve data transmission efficiency and reliability.

[0097] Through the above process, in practical applications, the transmitting end of this invention classifies and manages the data stream using a stream classifier, compresses the data packet header using the ROHC compressor engine, and achieves data aggregation and transmission through an aggregation queue manager and an aggregation frame constructor. The receiving end then disassembles the aggregation frames using an aggregation frame parser, restores the original data format using the ROHC decompressor engine, and dynamically optimizes the entire system using a feedback processor. Through the collaborative work of these modules, problems such as high protocol header overhead, redundant transmissions, high bit error rates, and long latency in satellite communication are effectively solved, improving the efficiency and reliability of data transmission.

[0098] The following are embodiments of the apparatus of the present invention, which can be used to execute the satellite communication transmission optimization method involved in the present invention. For details not disclosed in the embodiments of the apparatus of the present invention, please refer to the method embodiments of the satellite communication transmission optimization method involved in the present invention.

[0099] Please refer to Figure 5. In this embodiment of the invention, a satellite communication transmission optimization device 800 is provided.

[0100] The satellite communication transmission optimization device 800 includes, but is not limited to: a stream context association module 810, a header compression and aggregation module 830, a transmission fault tolerance optimization module 850, and a multi-service dynamic scheduling module 870.

[0101] The flow context association module 810 is used to acquire data packets. It extracts the header 5-tuple of the data packet and queries the flow context table. If the query matches the 5-tuple, the data packet is associated with the matched flow context; otherwise, a new flow context is created and the data is updated synchronously. The 5-tuple includes the source IP address, destination IP address, source port, destination port, and protocol type.

[0102] The header compression and aggregation module 830 is used to compress the header of the data packet to generate compressed data segments and store them in a FIFO queue. When the size or duration of the FIFO queue meets the set requirements, the data segments in the FIFO queue are encapsulated into an aggregate frame, and FEC encoding is added before it is sent to the link layer.

[0103] The transmission fault tolerance optimization module 850 is used to optimize transmission by increasing the number of IR packet transmissions when the bit error rate exceeds a set threshold, dynamically adjusting the compressor state according to the quality of the transmission link, sending a lightweight NACK when a minor anomaly occurs, and periodically cleaning the flow context table. Minor anomalies include packet loss and decompression failure. Minor anomalies include packet loss rate higher than a set value and decompression failure rate higher than a set value. IR packets are control packets used for ROHC context initialization and refresh.

[0104] The multi-service dynamic scheduling module 870 is used to divide priorities according to service type and configure aggregation parameters for different priorities. It reads TCP layer status information in real time and dynamically adjusts aggregation parameters, automatically marking NACK packets as the highest priority. Aggregation parameters include timeout threshold and size threshold.

[0105] It should be noted that the satellite communication transmission optimization provided in the above embodiments is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed. That is, the internal structure of the satellite communication transmission optimization device will be divided into different functional modules to complete all or part of the functions described above.

[0106] Furthermore, the satellite communication transmission optimization device and the satellite communication transmission optimization method provided in the above embodiments belong to the same concept, and the specific way in which each module performs its operation has been described in detail in the method embodiments, and will not be repeated here.

[0107] Figure 6 shows a schematic diagram of the structure of an electronic device according to an exemplary embodiment.

[0108] It should be noted that this electronic device is merely an example adapted to the present invention and should not be construed as providing any limitation on the scope of the invention. Furthermore, this electronic device should not be interpreted as requiring or needing to have one or more of the components of the exemplary electronic device 2000 shown in FIG. 6.

[0109] The hardware structure of the electronic device 2000 can vary greatly depending on the configuration or performance. As shown in Figure 6, the electronic device 2000 includes: a power supply 210, an interface 230, at least one memory 250, and at least one central processing unit (CPU) 270.

[0110] Specifically, power supply 210 is used to provide operating voltage for various hardware devices on electronic device 2000.

[0111] Interface 230 includes at least one wired or wireless network interface 231 for interacting with external devices. Of course, in other examples adapted to this invention, interface 230 may further include at least one serial-to-parallel conversion interface 233, at least one input / output interface 235, and at least one USB interface 237, as shown in FIG6, but this is not intended to be a specific limitation.

[0112] The memory 250 serves as a carrier for resource storage and can be a read-only memory, random access memory, disk, or optical disk, etc. The resources stored on it include the operating system 251, application programs 253, and data 255, etc., and the storage method can be temporary storage or permanent storage.

[0113] The operating system 251 is used to manage and control the various hardware devices and application programs 253 on the electronic device 2000, so as to enable the central processing unit 270 to perform calculations and processing on the massive data 255 in the memory 250. It can be Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, etc.

[0114] Application 253 is a computer-readable instruction based on operating system 251 that performs at least one specific task. It may include at least one module (not shown in Figure 6), and each module may contain computer-readable instructions for electronic device 2000. For example, a satellite communication transmission optimization device can be considered as application 253 deployed on electronic device 2000.

[0115] Data 255 may be signal information, etc., and is stored in memory 250.

[0116] The central processing unit 270 may include one or more processors and is configured to communicate with the memory 250 via at least one communication bus to read computer-readable instructions stored in the memory 250, thereby performing operations and processing on massive amounts of data 255 stored in the memory 250. For example, a satellite communication transmission optimization method can be implemented by the central processing unit 270 reading a series of computer-readable instructions stored in the memory 250.

[0117] Furthermore, the present invention can also be implemented through hardware circuits or a combination of hardware circuits and software. Therefore, the implementation of the present invention is not limited to any specific hardware circuit, software, or combination thereof.

[0118] Please refer to Figure 7. In this embodiment of the invention, an electronic device 4000 is provided. The electronic device 4000 may include: a desktop computer, a laptop computer, a server, etc., with sensor recognition capabilities.

[0119] In Figure 7, the electronic device 4000 includes at least one processor 4001 and at least one memory 4003.

[0120] Data interaction between the processor 4001 and the memory 4003 can be achieved through at least one communication bus 4002. This communication bus 4002 may include a path for transmitting data between the processor 4001 and the memory 4003. The communication bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus 4002 can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is used in Figure 7, but this does not indicate that there is only one bus or one type of bus.

[0121] Optionally, the electronic device 4000 may further include a transceiver 4004, which can be used for data interaction between the electronic device and other electronic devices, such as sending and / or receiving data. It should be noted that in practical applications, the transceiver 4004 is not limited to one type, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0122] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this invention. Processor 4001 may also be a combination that implements computing functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0123] The memory 4003 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program instructions or code in the form of instructions or data structures and accessible by the electronic device 4000, but not limited thereto.

[0124] The memory 4003 stores computer-readable instructions, and the processor 4001 can read the computer-readable instructions stored in the memory 4003 through the communication bus 4002.

[0125] The computer-readable instructions are executed by one or more processors 4001 to implement the satellite communication transmission optimization methods in the above embodiments.

[0126] Furthermore, this embodiment of the invention provides a storage medium storing computer-readable instructions, which are executed by one or more processors to implement the satellite communication transmission optimization method described above.

[0127] This invention provides a computer program product, which includes computer-readable instructions stored in a storage medium. One or more processors of an electronic device read the computer-readable instructions from the storage medium, load and execute the computer-readable instructions, thereby enabling the electronic device to implement the satellite communication transmission optimization method as described above.

[0128] Compared with related technologies, the beneficial effects of this invention are: 1. This invention can effectively reduce bandwidth waste; through a pipelined processing method of "header compression to reduce single packet overhead → data packet aggregation to reduce transmission frequency", it optimizes both "single packet cost" and "transmission frequency". The stream classifier accurately manages the data stream, the ROHC compressor engine compresses the data packet header to reduce single packet overhead, and the aggregation queue manager and aggregation frame constructor aggregate and transmit the compressed data segments to reduce the number of transmissions, thereby significantly reducing bandwidth waste.

[0129] 2. This invention exhibits high transmission robustness through the design of a fast context synchronization mechanism, adaptive state transition and fault-tolerant coding, and lightweight exception handling and resource management mechanisms. The fast context synchronization mechanism ensures that the receiver quickly captures context information through redundant IR packet transmission; the adaptive state transition and fault-tolerant coding enable the compressor to dynamically adjust its state based on link quality, and combined with the error tolerance capability of W-LSB coding, it reduces decompression failures; the lightweight exception handling and resource management mechanism ensures stable operation of the system under high error rate scenarios through operations such as sequence number detection of packet loss, sending lightweight NACK notifications to the sender for adjustment, and cleaning up invalid flow context tables.

[0130] 3. This invention can meet the QoS requirements of multiple services by implementing a multi-priority hybrid triggering aggregation strategy. The flow classifier divides services into different priorities based on multiple rules, configures differentiated aggregation parameters for queues of different priorities, adopts a hierarchical scheduling strategy to ensure reasonable resource allocation, and automatically marks NACK packets as the highest priority, achieving precise adaptation of "high priority to ensure latency and low priority to improve efficiency" to meet the differentiated transmission requirements of multiple satellite services.

[0131] 4. This invention achieves organic synergy between compression and aggregation technologies by constructing a feedback-driven cross-layer collaborative mechanism. The compression layer and TCP layer work together in real time. The compressor reads TCP layer status information and triggers aggregation layer parameter adjustment when a link deterioration signal is detected. The compression layer and aggregation layer achieve parameter linkage optimization, adjusting the aggregation strategy according to the compressor status. The feedback layer and aggregation layer work together to improve feedback efficiency. NACK packets are automatically marked as high priority and sent immediately, forming an optimization closed loop and improving the overall system performance.

[0132] 5. This invention improves bandwidth utilization. Through the combined effect of the above-mentioned series of technical means, it effectively optimizes the data transmission process, reduces invalid transmissions and resource waste, and makes fuller use of bandwidth, maintaining a high bandwidth utilization rate even in high error rate scenarios, while solving bandwidth waste, improving transmission robustness, meeting the QoS requirements of multiple services, and achieving technical synergy.

[0133] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0134] The above description is only a partial embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A satellite communication transmission optimization method, characterized in that, The method includes: acquiring data packets; extracting the header 5-tuple of the data packets and querying a flow context table; if the query matches the 5-tuple, associating the data packet with the matched flow context; otherwise, creating a new flow context and synchronously updating the data; the 5-tuple includes source IP address, destination IP address, source port, destination port, and protocol type; compressing the header of the data packets to generate compressed data segments and storing them in a FIFO queue; when the size or duration of the FIFO queue meets set requirements, encapsulating the data segments in the FIFO queue into an aggregate frame, adding FEC encoding, and sending it to the link layer; and controlling errors... When the bit rate exceeds a set threshold, the number of IR packet transmissions is increased; the compressor state is dynamically adjusted according to the quality of the transmission link; a lightweight NACK is sent when a minor anomaly occurs; and the flow context table is cleaned periodically for transmission optimization. The minor anomalies include packet loss rate higher than a set value and decompression failure rate higher than a set value. The IR packets are control packets used for ROHC context initialization and refresh. Priorities are divided according to service type, and aggregation parameters are configured for different priorities. TCP layer status information is read in real time and aggregation parameters are dynamically adjusted. The NACK packets are automatically marked as the highest priority. The aggregation parameters include timeout threshold and size threshold.

2. The satellite communication transmission optimization method as described in claim 1, characterized in that, The process of extracting the IP / TCP header 5-tuple from the data packet and querying the flow context table, where the data packet is associated with the matching flow context if the query finds a match, and a new flow context is created and the data is updated synchronously, includes: extracting the IP / TCP header 5-tuple from the data packet, querying the flow context table for the 5-tuple, and if the 5-tuple already exists, directly associating the data packet with the corresponding flow context; if the 5-tuple does not exist, creating a new flow context in the flow context table based on the 5-tuple, updating the 5-tuple in the flow context table, and synchronously updating the status information of the flow context table.

3. The satellite communication transmission optimization method as described in claim 1, characterized in that, The process of compressing the header of the data packet to generate a compressed data segment and storing it in a FIFO queue, and encapsulating the data segments in the FIFO queue into an aggregate frame when the size or duration of the FIFO queue meets the set requirements, includes: retrieving the context data of the flow context corresponding to the data packet from the flow context table through the ROHC compressor; compressing the header of the data packet according to the context data to generate a compressed data segment containing a context identifier (CID); storing the compressed data segment in the FIFO queue of the flow context corresponding to the data packet; monitoring the size and duration of the queue; and if the size reaches a set size threshold or the duration reaches a set timeout threshold, encapsulating all data segments in the FIFO queue into an aggregate frame containing a sequence number and the number of data segments.

4. The satellite communication transmission optimization method as described in claim 1, characterized in that, The step of increasing the number of IR packet transmissions when the bit error rate exceeds a set threshold includes: real-time monitoring of the bit error rate of the transmission link and comparing it with a preset threshold; if the bit error rate exceeds the threshold, the number of IR packet transmissions is increased; the increase in the number of IR packet transmissions is used to ensure that the receiving end can quickly capture context information.

5. The satellite communication transmission optimization method as described in claim 1, characterized in that, The steps of dynamically adjusting the compressor state based on the quality of the transmission link, sending a lightweight NACK when a minor anomaly occurs, and periodically cleaning the flow context table include: monitoring link anomaly signals transmitted by the TCP layer in the transmission link and predicting link deterioration trends; the anomaly signals include ACK acknowledgment timeout and increased data packet retransmission count; when the link deterioration trend exceeds a set condition, the compressor state is downgraded and more context information is sent for resynchronization; when decompression failure or frame corruption occurs, a lightweight NACK containing only a frame corruption identifier is sent to the sending end, the compressor state is downgraded, and resynchronization is performed.

6. The satellite communication transmission optimization method as described in claim 1, characterized in that, The step of prioritizing services based on service type and configuring aggregation parameters for different priorities includes: dividing services into highest priority, second-highest priority, and lowest priority based on service information; the service information includes a 5-tuple, a DSCP tag, and a port number; configuring a minimum timeout threshold and a minimum size threshold for the highest priority service; configuring a maximum timeout threshold and a maximum size threshold for the lowest priority service; using strict priority scheduling for the highest priority queue, and using weighted fair queue scheduling for the second-highest and lowest priority queues according to set weights; the configuration of the weights is dynamically adjusted according to the service type.

7. The satellite communication transmission optimization method as described in claim 4, characterized in that, The real-time reading of TCP layer status information and dynamic adjustment of aggregation parameters, automatically marking the NACK packet as the highest priority, includes: real-time reading of TCP layer status information to detect whether a link deterioration signal has occurred; the status information includes ACK timeout count, retransmission counter, and congestion window changes; when link deterioration is detected, dynamic adjustment of aggregation parameters is triggered; the dynamic adjustment of aggregation parameters includes increasing queue priority and shortening timeout threshold; automatically marking the generated NACK packet as the highest priority, the NACK packet including decompression failure information and frame corruption information.

8. A satellite communication transmission optimization device, characterized in that, The device includes: a flow context association module, used to acquire data packets, extract the header 5-tuple of the data packet and query the flow context table; if the query matches the 5-tuple, the data packet is associated with the matching flow context; otherwise, a new flow context is created and the data is updated synchronously; the 5-tuple includes source IP address, destination IP address, source port, destination port, and protocol type; a header compression and aggregation module, used to compress the header of the data packet to generate compressed data segments and store them in a FIFO queue; when the size or duration of the FIFO queue meets the set requirements, the data segments in the FIFO queue are encapsulated into an aggregate frame, FEC encoding is added, and then the frame is sent to the link layer; transmission fault tolerance. The optimization module is used to optimize transmission by increasing the number of IR packet transmissions when the bit error rate exceeds a set threshold, dynamically adjusting the compressor state according to the quality of the transmission link, sending a lightweight NACK when a minor anomaly occurs, and periodically cleaning the flow context table; the minor anomaly includes a packet loss rate higher than a set value and a decompression failure rate higher than a set value; the IR packet is a control packet used for ROHC context initialization and refresh; the multi-service dynamic scheduling module is used to prioritize services according to service type and configure aggregation parameters for different priorities, read TCP layer status information in real time and dynamically adjust aggregation parameters, and automatically mark the NACK packet as the highest priority; the aggregation parameters include a timeout threshold and a size threshold.

9. An electronic device, characterized in that, include: At least one processor and at least one memory, wherein computer-readable instructions are stored on the memory; the computer-readable instructions are executed by one or more of the processors to cause the electronic device to implement the satellite communication transmission optimization method as described in any one of claims 1 to 7.

10. A storage medium having computer-readable instructions stored thereon, characterized in that, The computer-readable instructions are executed by one or more processors to implement the satellite communication transmission optimization method as described in any one of claims 1 to 7.

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