System and method for efficiently decoding RRC (Radio Resource Control) message based on dynamic configuration

Abstract

The invention belongs to the technical field of message decoding, and particularly relates to an efficient RRC message decoding system and method based on dynamic configuration, and the system comprises a scene sensing module which collects the operation state and communication environment information of communication equipment in real time, processes the collected information, and abstracts a current communication scene into a group of feature vectors; the configuration generation module is used for combining the feature vector with a pre-stored RRC protocol rule base to generate a decoding configuration file for the current scene; the resource management module is used for distributing and dynamically managing computing resources and memory resources of the system according to the decoding configuration file; the decoding execution module is used for decoding the RRC message according to the decoding configuration file and the resources distributed by the resource management module; and the self-adaptive learning module is used for realizing decoding by analyzing and learning a new rule when the decoding operation cannot correctly decode so as to improve the compatibility of the system. According to the invention, compatibility and decoding efficiency can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of message decoding, in particular to a high-efficiency decoding system and method for RRC messages based on dynamic configuration. BACKGROUND

[0002] At present, the rapid development of mobile wireless network communication makes the wireless communication protocol data payload larger and larger, and the parsing ability of protocol data higher and higher. Most of the existing technologies adopt full-amount decoding mode, and the traditional recursive descent decoding algorithm has high time complexity and significantly reduced performance when processing complex nested structures.

[0003] With the continuous updating of wireless communication standards, the RRC (Radio Resource Control) protocol will also be revised and expanded. Whenever the protocol changes, even if only a small adjustment is made to the format, meaning or value range of a parameter, the traditional decoding method usually needs to make large-scale code modification and debugging to the entire decoding program, and the compatibility is poor. This not only increases the cost of software development and maintenance, prolongs the development cycle, but also easily introduces new errors in the modification process, affects the reliability and stability of the system, and causes low decoding efficiency. SUMMARY

[0004] In view of the technical defects mentioned in the background art, the purpose of the embodiments of the present application is to provide a high-efficiency decoding system and method for RRC messages based on dynamic configuration, so as to improve the decoding efficiency.

[0005] To achieve the above-mentioned purpose, in a first aspect, the embodiments of the present application provide a high-efficiency decoding system for RRC messages based on dynamic configuration, which comprises:

[0006] A scene perception module is configured to collect the running state and communication environment information of a communication device in real time, process the collected information, and abstract the current communication scene as a set of feature vectors;

[0007] A configuration generation module is configured to combine the feature vectors with a pre-stored RRC protocol rule library to generate a decoding configuration file for the current scene; wherein the RRC protocol rule library includes detailed rules of RRC protocols under multiple versions and multiple application scenarios;

[0008] A resource management module is configured to allocate and dynamically manage the computing resources and memory resources of the system according to the decoding configuration file generated by the configuration generation module;

[0009] A decoding execution module is configured to decode RRC messages according to the decoding configuration file and the resources allocated by the resource management module;

[0010] An adaptive learning module is configured to analyze and learn new rules to realize decoding when the decoding operation cannot correctly decode, to improve the compatibility of the system, and to feed back the new rules to the configuration generation module to realize self-optimization of the system.

[0011] As a specific implementation manner of the present application, the scene perception module specifically comprises:

[0012] An information collection unit is configured to collect information related to communication equipment and communication environment through various channels, to interact with a GPS module built in the communication equipment to obtain geographical position, moving speed and direction information of the equipment, to determine whether the communication equipment is in a high-speed moving scene, to obtain network parameters of a currently connected network through a network interface, and to interact with an upper application program to understand a currently running communication service.

[0013] An information processing and feature extraction unit is configured to normalize various collected information, to convert the information into a unified data format, to extract a plurality of key features from the processed information by using a preset feature extraction algorithm, and to form a feature vector by using the key features to comprehensively describe a current communication scene.

[0014] As a specific implementation manner of the present application, the configuration generation module specifically comprises:

[0015] A rule matching unit is configured to accurately match in the RRC protocol rule library according to the output feature vector, to find out an RRC message type closely related to a current communication scene and a corresponding parameter set of the RRC message type.

[0016] A configuration file generation unit is configured to determine an accurate position of each parameter in an RRC message, a data type of the parameter and applicable decoding algorithm information based on the filtered parameter set, and to generate the decoding configuration file by arranging the information in a preset format.

[0017] As a specific implementation manner of the present application, the resource management module specifically comprises:

[0018] A priority determination unit is configured to determine a priority of each parameter decoding task according to the generated decoding configuration file, wherein a parameter decoding task with high real-time requirement and great influence on communication quality is given a high priority, and a non-key auxiliary parameter decoding task is given a low priority.

[0019] A computing resource allocation unit is configured to monitor the information of the currently available computing resources of the system in real time, and allocate CPU time slices and core resources for each decoding task according to the priority of the decoding task and a preset scheduling algorithm; for a high-priority task, more CPU time slices and cores with better performance are allocated to ensure that the task is executed preferentially and quickly.

[0020] A memory resource allocation unit is configured to allocate a corresponding memory space for each decoding task according to the size of each parameter, the amount of intermediate data expected to be generated during the decoding process, and the storage requirement.

[0021] Meanwhile, memory reuse and caching techniques are adopted to release the memory for the decoded data that is not used temporarily, and to manage the caching of the intermediate data that needs to be reused, so as to avoid memory waste and fragmentation.

[0022] As a specific implementation manner of the present application, the decoding execution module specifically comprises:

[0023] A message reading and parameter positioning unit is configured to read the RRC message from the communication link, and to accurately locate the storage position of each parameter in the message according to the position information of each parameter in the decoding configuration file.

[0024] A parameter decoding unit is configured to perform decoding operation on each located parameter according to the data type and decoding algorithm determined in the decoding configuration file.

[0025] A checking and error handling unit is configured to perform real-time checking on the decoding result of each parameter during the decoding process.

[0026] As a specific implementation manner of the present application, the adaptive learning module specifically comprises:

[0027] An abnormal message capturing unit is configured to pass the RRC message that cannot be decoded correctly by the decoding execution module according to the existing decoding configuration file to the adaptive learning module.

[0028] A feature extraction and analysis unit is configured to comprehensively extract the features of the RRC message that cannot be decoded correctly, and then compare the extracted features with the stored RRC protocol rule library and other variant rules learned from history in detail to analyze the differences between the message and the existing rules.

[0029] A rule learning and updating unit is configured to realize decoding of the message by adjusting existing decoding parameters or learning brand-new decoding rules, wherein the process comprises multiple tentative decodings of the message and result verification; once an effective decoding method is found, the newly learned rule or parameter adjustment is recorded and updated into the RRC protocol rule library; meanwhile, the new rule is fed back to the configuration generation module so that the new message variant condition can be considered when generating a decoding configuration file subsequently, thereby improving the decoding capability of the system for different RRC message variants.

[0030] In a second aspect, the embodiments of the present application further provide a high-efficiency decoding method for RRC messages based on dynamic configuration, which is applied to the high-efficiency decoding system for RRC messages based on dynamic configuration in the first aspect, and comprises the following steps:

[0031] Real-time collection of running states of communication devices and communication environment information, and processing of the collected information to abstract the current communication scenario into a group of feature vectors;

[0032] Combination of the feature vectors with a pre-stored RRC protocol rule library to generate a decoding configuration file for the current scenario; wherein the RRC protocol rule library comprises RRC protocol detailed rules in multiple versions and multiple application scenarios;

[0033] Allocation and dynamic management of computing resources and memory resources of the system according to the decoding configuration file generated by the configuration generation module;

[0034] Decoding operation on RRC messages according to the decoding configuration file and the resources allocated by the resource management module;

[0035] When the decoding operation cannot correctly decode, new rules are analyzed and learned to realize decoding, so as to improve the compatibility of the system, and the new rules are fed back to the configuration generation module to realize self-optimization of the system.

[0036] The technical scheme provided by the embodiments of the present application abstracts the current communication scenario into a group of feature vectors according to real-time requirements of the communication scenario; then the feature vectors are combined with a pre-stored RRC protocol rule library to generate a decoding configuration file for the current scenario, so that subsequent decoding can be realized by preferentially decoding key feature parts in RRC messages, thereby avoiding invalid processing of redundant information and significantly improving decoding speed and efficiency; meanwhile, when a message cannot be decoded, new rules are analyzed and learned to improve the compatibility of the system, and the new rules are fed back to the configuration generation module to realize self-optimization of the system; through such a modular and intelligent solution, high-efficiency, low-consumption, flexible and compatible decoding of RRC messages is realized. BRIEF DESCRIPTION OF DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the specific embodiments or prior art of the present application, the drawings needed in the specific embodiment or prior art description will be briefly introduced as follows.

[0038] Figure 1 is a principle block diagram of a system for efficient decoding of RRC messages based on dynamic configuration provided by an embodiment of the present application;

[0039] Figure 2 is a process schematic diagram of a system for efficient decoding of RRC messages based on dynamic configuration provided by an embodiment of the present application;

[0040] Figure 3 is a flowchart of a method for efficient decoding of RRC messages based on dynamic configuration provided by an embodiment of the present application. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0042] It should be understood that, when used in the present specification and the appended claims, the terms "comprise" and "include" indicate the presence of the described features, integers, steps, operations, elements, and / or components, but do not exclude one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0043] Please refer to Figure 1 and Figure 2 The system for efficient decoding of RRC messages based on dynamic configuration provided by the embodiments of the present application comprises:

[0044] A scene perception module is configured to collect running states of communication devices and communication environment information in real time, and process the collected information to abstract the current communication scene as a set of feature vectors;

[0045] A configuration generation module is configured to combine the feature vectors with a pre-stored RRC protocol rule library to generate a decoding configuration file for the current scene; wherein the RRC protocol rule library comprises RRC protocol detailed rules under multiple versions and multiple application scenarios;

[0046] A resource management module is configured to allocate and dynamically manage computing resources and memory resources of the system according to the decoding configuration file generated by the configuration generation module.

[0047] a decoding execution module configured to decode the RRC message according to the decoding configuration file and the resources allocated by the resource management module;

[0048] an adaptive learning module configured to, when the decoding operation cannot be decoded correctly, implement decoding by analyzing and learning new rules to improve the compatibility of the system, and feed back the new rules to the configuration generation module to realize self-optimization of the system.

[0049] In the embodiment, the scene awareness module specifically comprises:

[0050] an information collection unit configured to collect information related to the communication device and the communication environment through various channels, and interact with the GPS module built in the communication device to obtain the geographical position, moving speed and direction information of the device, so as to determine whether the communication device is in a high-speed moving scene; obtain the network parameters of the currently connected network through the network interface; and interact with the upper application program to understand the currently running communication service;

[0051] The network parameters include network related parameters such as the network standard (such as 4G, 5G) of the currently connected network, signal strength, bandwidth, etc.; and the communication service is, for example, real-time voice call, high-definition video streaming, ordinary data download, or low-power data interaction between Internet of Things devices, etc.

[0052] an information processing and feature extraction unit configured to normalize the collected various types of information, convert them into a unified data format, and then use a preset feature extraction algorithm to extract a plurality of key features from the processed information, and then form a feature vector composed of the plurality of key features, which is used to comprehensively describe the current communication scene. For example, for a scene of high-speed movement and video call, the feature vector may include key features such as moving speed exceeding a certain threshold, service type being video call, network signal strength being in a certain interval, etc.

[0053] The configuration generation module specifically comprises:

[0054] a rule matching unit configured to accurately match in the RRC protocol rule library according to the output feature vector, and find out the RRC message type closely related to the current communication scene and the corresponding parameter set; for example, if the scene awareness module determines that the device is in a high-speed moving state and is performing a video call, the configuration generation module will find out the RRC messages related to mobility management and video transmission from the rule library; such as the part related to the handover parameters (such as handover threshold, neighbor list), video encoding parameters in the RRC connection reconfiguration message, and the parameters related to the video transmission quality guarantee (such as encoding mode, resource allocation parameters).

[0055] The configuration file generating unit is configured to determine the accurate position (expressed in byte offset or bit position) of each parameter in the RRC message, the data type (such as unsigned integer, enumeration type, string, etc.) and the applicable decoding algorithm (for example, specific binary decoding algorithm, lookup table decoding algorithm) and other detailed information based on the screened parameter set, and to generate the decoding configuration file by arranging these information in a preset format; the decoding configuration file adopts a format easy to read and parse, such as XML or JSON format, which contains specific configuration items of each decoding parameter, such as "parameter name: switching threshold, position: 10-13 bytes of the message body, data type: unsigned integer, decoding algorithm: value conversion after bit-by-bit parsing".

[0056] Through in-depth analysis of the RRC protocol and real-time perception of the communication scene demand, dynamic adjustment of the decoding configuration is realized. Specifically, before receiving the RRC message, the system will predict the key information that may need to be parsed according to the current state of the communication device (such as whether it is in a mobile state, the type of network currently connected, etc.), the type of communication service (such as voice call, video streaming, data download, etc.) and the pre-stored RRC protocol rule library, and generate the corresponding decoding configuration file. For example, when the device is in a high-speed mobile state and is making a video call, the system will predict that RRC messages related to mobility management and video transmission may be frequently received, and thus will focus on configuring fast parsing rules for these related parameters in the decoding configuration file. In this way, in the actual decoding process, the system can prioritize decoding the key parts of the RRC message and skip the redundant information that is not likely to be used in the current scenario, greatly improving the decoding efficiency.

[0057] The resource management module specifically includes:

[0058] The priority determination unit is configured to determine the priority of each parameter decoding task according to the generated decoding configuration file; wherein parameter decoding tasks with high real-time requirements and large impact on communication quality are given high priority, while some non-critical auxiliary parameter decoding tasks have low priority; for example, in real-time video calls, the decoding tasks related to video encoding parameters have higher priority than the non-critical parameter decoding tasks for statistical purposes.

[0059] A computing resource allocation unit is configured to monitor the current computing resource information (e.g., the number of currently available CPU cores, the operation frequency, etc.) of the system in real time, and allocate CPU time slices and core resources for each decoding task according to the priority of the decoding task and a preset scheduling algorithm (e.g., a priority-based preemptive scheduling algorithm). For a high-priority task, more CPU time slices and cores with higher performance are allocated to ensure that the task is executed in priority and quickly. For example, the CPU time slices and core resources are allocated to each decoding task according to the priority order, and a plurality of high-performance CPU cores are allocated to the video encoding parameter decoding task with the highest priority, and a longer continuous time slice is given for operation.

[0060] A memory resource allocation unit is configured to allocate a corresponding memory space for each decoding task according to the size of each parameter, the amount of intermediate data generated during the decoding process, and the storage requirement.

[0061] Meanwhile, memory reuse and caching techniques are adopted to release the memory of the decoded data that is not used temporarily in time, and to manage the caching of the intermediate data that needs to be reused, so as to avoid memory waste and fragmentation. For example, when decoding a large RRC message, the memory space occupied by the temporary data structure used only in a specific stage is recycled immediately after use for use by other tasks.

[0062] In application, the decoding execution module specifically includes:

[0063] A message reading and parameter positioning unit is configured to read the RRC message from the communication link, and accurately locate the storage position of each parameter in the message according to the position information of each parameter in the decoding configuration file. For example, for the switching threshold parameter with the specified position of “10-13 bytes” in the configuration file, the decoding execution module directly extracts 4 bytes of data from the 10th byte of the RRC message as the original data of the parameter.

[0064] A parameter decoding unit is configured to decode each parameter located according to the data type and decoding algorithm determined in the decoding configuration file. For example, for an unsigned integer parameter encoded in the form of binary complement, the decoding execution module converts the binary data into a decimal value according to the corresponding decoding algorithm. When decoding complex data structures (e.g., nested structures, arrays), the decoding is performed step by step according to the defined structure hierarchy and element parsing rules.

[0065] A check and error handling unit is configured to check the decoding result of each parameter in real time during the decoding process. The check includes whether the data format is consistent with the expectation (e.g., whether an integer is within a specified value range, whether the length of a string is correct), and logical consistency with other related parameters (e.g., whether the logical relationship between a switching threshold and a neighbor signal strength is reasonable). If an error is found during the check, the error is handled according to a preset error handling mechanism. For minor errors, such as a small deviation in the data format but not affecting the overall understanding, the decoding is corrected by an error correction algorithm. For serious errors, such as a key parameter value exceeding a reasonable range, detailed error logs (including error parameter name, location, actual decoding value, expected value, and other information) are recorded and reported to the system, and the current decoding task is suspended, waiting for further processing (e.g., reacquiring a message, manual intervention, etc.).

[0066] In this embodiment, the adaptive learning module specifically includes:

[0067] An abnormal message capturing unit is configured to pass an RRC message that cannot be correctly decoded by the decoding execution module according to an existing decoding configuration file to the adaptive learning module (equivalent to the case where the decoding is determined to be unsuccessful). These abnormal messages can be caused by slight changes in the RRC protocol, new operator customization formats, or device-specific encoding methods.

[0068] A feature extraction and analysis unit is configured to comprehensively extract features of the RRC message that cannot be correctly decoded. Then, the extracted features are compared in detail with the stored RRC protocol rule library and other variant rules learned from history to analyze the differences between the message and the existing rules.

[0069] Specifically, the abnormal message is comprehensively extracted for features, including the overall structure of the message (e.g., field arrangement order, hierarchical relationship), parameter distribution rule (e.g., parameter frequency, correlation between adjacent parameters), data encoding method (e.g., whether a new encryption algorithm or special binary encoding rule is used), and the like. Then, the extracted features are compared in detail with the stored standard RRC protocol rules and other variant rules learned from history to analyze the differences between the message and the existing rules.

[0070] A rule learning and updating unit is configured to realize decoding of the message by adjusting existing decoding parameters or learning brand-new decoding rules, wherein the process comprises multiple tentative decodings of the message and result verification (for example, tentative decoding is performed by changing a decoding algorithm of a certain parameter, adjusting a parameter position, or redefining a data type, etc.); once an effective decoding method is found, the newly learned rule or parameter adjustment is recorded and updated into the RRC protocol rule library; meanwhile, the new rule is fed back to the configuration generation module so that the new message variant condition can be considered in subsequent generation of a decoding configuration file, thereby improving decoding capability of the system on different RRC message variants.

[0071] The above scheme abstracts the current communication scenario into a group of feature vectors according to real-time requirements of the communication scenario; then the feature vectors are combined with the pre-stored RRC protocol rule library to generate a decoding configuration file for the current scenario, so that subsequent decoding can be performed on a key feature part in the RRC message preferentially, thereby avoiding invalid processing of redundant information, and significantly improving decoding speed and efficiency; meanwhile, when a message that cannot be decoded is encountered, the system compatibility is improved by analyzing and learning new rules, and the new rules are fed back to the configuration generation module to realize self-optimization of the system; through the modular and intelligent solution, efficient, low-consumption, flexible and compatible decoding of the RRC message is realized.

[0072] Based on the same inventive concept, the embodiment of the application further provides an efficient decoding method for RRC messages based on dynamic configuration, applied to the efficient decoding system for RRC messages based on dynamic configuration in the first aspect, and referring to Figure 3 , the method comprises the following steps:

[0073] S101, real-time collection of running states of communication devices and communication environment information, and processing of the collected information to abstract the current communication scenario into a group of feature vectors;

[0074] S102, combination of the feature vectors with a pre-stored RRC protocol rule library to generate a decoding configuration file for the current scenario; wherein the RRC protocol rule library comprises RRC protocol detailed rules in multiple versions and multiple application scenarios;

[0075] S103, allocation and dynamic management of computing resources and memory resources of the system according to the decoding configuration file generated by the configuration generation module;

[0076] S104, decoding operation on the RRC message according to the decoding configuration file and the resources allocated by the resource management module;

[0077] S105, when the decoding operation cannot be correctly decoded, new rules are analyzed and learned to realize decoding, so as to improve the compatibility of the system, and the new rules are fed back to the configuration generation module to realize self-optimization of the system.

[0078] Further, the current communication scenario is abstracted as a set of feature vectors, specifically including:

[0079] Through various ways, the communication device and the communication environment related information are collected, and the geographic position, moving speed and direction information of the device are obtained by interacting with the GPS module built in the communication device, so that whether the communication device is in a high-speed moving scenario is judged; the network parameters of the current connection are obtained through the network interface; at the same time, information interaction is carried out with the upper application program to understand the communication service currently running;

[0080] The collected various information is normalized and converted into a unified data format; then, a plurality of key features are extracted from the processed information by using a preset feature extraction algorithm, and a set of feature vectors are formed by the plurality of key features, which are used to comprehensively describe the current communication scenario.

[0081] In this embodiment, the decoding configuration file is generated, specifically including:

[0082] According to the output feature vector, accurate matching is carried out in the RRC protocol rule library to find out the RRC message type closely related to the current communication scenario and the corresponding parameter set;

[0083] The configuration file generation unit is used to determine the accurate position of each parameter in the RRC message, the data type and the applicable decoding algorithm information based on the screened parameter set, and to generate the decoding configuration file by arranging these information in a preset format.

[0084] By analyzing and learning new rules to realize decoding, the compatibility of the system is improved, and the following steps are processed:

[0085] The RRC message that cannot be correctly decoded is comprehensively feature extracted; then, the extracted features are compared in detail with the stored RRC protocol rule library and other variant rules learned from history, and the difference between the message and the existing rules is analyzed;

[0086] Then, the decoding of the message is realized by adjusting the existing decoding parameters or learning brand-new decoding rules; wherein, the process includes multiple trial decoding of the message and result verification; once the effective decoding method is found, the newly learned rules or parameter adjustment are recorded and updated to the RRC protocol rule library;

[0087] Meanwhile, the new rule is fed back to the configuration generation module, so that the new message variant condition can be considered when generating the decoding configuration file subsequently, thereby improving the decoding capability of the system on different RRC message variants.

[0088] It should be noted that the more specific workflow of the method embodiment is described in the foregoing system embodiment, and will not be described here.

[0089] The whole scheme abstracts the current communication scenario into a set of feature vectors according to the real-time requirement of the communication scenario; then combines the feature vectors with the pre-stored RRC protocol rule library to generate a decoding configuration file for the current scenario, realizes the subsequent decoding to preferentially decode the key feature part in the RRC message, avoids the invalid processing on the redundant information, thereby significantly improves the decoding speed and efficiency; meanwhile, when encountering a message that cannot be decoded, the compatibility of the system is improved by analyzing and learning the new rule.

[0090] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited to this, any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A system for efficient decoding of RRC messages based on dynamic configuration, characterized in that, The system comprises: a scene awareness module for collecting the running state of the communication device and the communication environment information in real time, processing the collected information, and abstracting the current communication scene as a set of feature vectors; a configuration generation module for combining the feature vectors with a pre-stored RRC protocol rule library to generate a decoding configuration file for the current scene; wherein the RRC protocol rule library comprises RRC protocol detailed rules in multiple versions and multiple application scenarios; a resource management module for allocating and dynamically managing the computing resources and memory resources of the system according to the decoding configuration file generated by the configuration generation module; a decoding execution module for decoding the RRC message according to the decoding configuration file and the resources allocated by the resource management module; an adaptive learning module for realizing decoding by analyzing and learning new rules when the decoding operation cannot correctly decode, so as to improve the compatibility of the system, and feeding back the new rules to the configuration generation module to realize self-optimization of the system.

2. The system of claim 1, wherein, The scene awareness module specifically comprises: an information collection unit for collecting communication device and communication environment related information through multiple channels, and interacting with the GPS module built-in the communication device to obtain the geographical position, moving speed and direction information of the device, so as to determine whether the communication device is in a high-speed moving scenario; obtaining the current connected network parameters through the network interface; and interacting with the upper application program to understand the currently running communication service; an information processing and feature extraction unit for normalizing the collected various types of information, converting them into a unified available data format; then, using a pre-set feature extraction algorithm, extracting a plurality of key features from the processed information, and then grouping the plurality of key features into a feature vector for comprehensively describing the current communication scene.

3. The system of claim 1, wherein, The configuration generation module specifically comprises: a rule matching unit for accurately matching in the RRC protocol rule library according to the output feature vector, finding out the RRC message type closely related to the current communication scene and the corresponding parameter set thereof; a configuration file generation unit for determining the accurate position of each parameter in the RRC message, the data type and the applicable decoding algorithm information based on the filtered parameter set, and arranging these information in a pre-set format to generate the decoding configuration file.

4. The system of claim 1, wherein, The resource management module specifically comprises: a priority determination unit for determining the priority of each parameter decoding task according to the generated decoding configuration file; wherein the parameter decoding tasks with high real-time requirements and great impact on communication quality are given high priority, while some non-critical auxiliary parameter decoding tasks have low priority; a computing resource allocation unit for monitoring the current available computing resource information of the system in real time, and allocating CPU time slices and core resources for each decoding task according to the priority of the decoding task and a pre-set scheduling algorithm; for high-priority tasks, more CPU time slices and cores with better performance are allocated to ensure that they can be executed preferentially and quickly; Memory resource allocation unit, for allocating corresponding memory space for each decoding task according to the size of each parameter, the amount of intermediate data expected to be generated in the decoding process and the storage requirement; At the same time, by using memory multiplexing and caching technology, the memory of the decoded data temporarily not used is released in time, and the intermediate data needing to be reused is managed by caching to avoid memory waste and fragmentation.

5. The system of claim 3, wherein, The decoding execution module specifically comprises: Message reading and parameter positioning unit, for reading RRC messages from the communication link, and accurately positioning the storage location of each parameter in the message according to the position information of each parameter in the decoding configuration file; Parameter decoding unit, for decoding each parameter positioned according to the data type and decoding algorithm determined in the decoding configuration file; Verification and error handling unit, for verifying the decoding result of each parameter in real time during the decoding process.

6. The system of any one of claims 1 to 5, wherein, The adaptive learning module specifically comprises: Abnormal message capturing unit, for passing the RRC message that the decoding execution module cannot decode correctly according to the existing decoding configuration file to the adaptive learning module; Feature extraction and analysis unit, for comprehensively extracting the features of the RRC message that cannot be decoded correctly; then, comparing the extracted features with the stored RRC protocol rule library and other learned variant rules in history in detail to analyze the differences between the message and the existing rules; Rule learning and updating unit, for realizing the decoding of the message by adjusting the existing decoding parameters or learning new decoding rules; wherein, the process includes multiple tentative decoding of the message and result verification; once an effective decoding method is found, the newly learned rule or parameter adjustment is recorded and updated to the RRC protocol rule library; at the same time, the new rule is fed back to the configuration generation module, so that the new message variant situation can be considered when generating the decoding configuration file in the future, thereby improving the decoding ability of the system to different RRC message variants. 7.A method for efficient decoding of a dynamic configuration based RRC message, the method comprising: The method is applied to the RRC message efficient decoding system based on dynamic configuration in claim 1, and the method comprises the following steps: Collecting the running state and communication environment information of the communication equipment in real time, and processing the collected information to abstract the current communication scene as a group of feature vectors; Combining the feature vectors with the pre-stored RRC protocol rule library to generate a decoding configuration file for the current scene; wherein, the RRC protocol rule library comprises detailed rules of RRC protocols under multiple versions and multiple application scenarios; Allocating and dynamically managing the computing resources and memory resources of the system according to the decoding configuration file generated by the configuration generation module; Decoding the RRC message according to the decoding configuration file and the resources allocated by the resource management module; When the decoding operation cannot correctly decode, new rules are analyzed and learned to realize decoding, so as to improve the compatibility of the system, and the new rules are fed back to the configuration generation module to realize self-optimization of the system.

8. The method of claim 7, wherein, The current communication scenario is abstracted as a set of feature vectors, specifically including: Through various ways to collect communication equipment and communication environment related information, and interact with the GPS module built-in communication equipment to obtain the geographical position, moving speed and direction information of the device, so as to judge whether the communication equipment is in a high-speed moving scene; Through the network interface to obtain the network parameters of the current connection; At the same time, interact with the upper application program to understand the current running communication service; The collected various information is normalized and converted into a unified data format; Then, a preset feature extraction algorithm is used to extract a plurality of key features from the processed information, and a set of feature vectors is formed to comprehensively describe the current communication scenario.

9. The method of claim 7, wherein, Generating the decoding configuration file, specifically including: According to the output feature vector, accurate matching is performed in the RRC protocol rule library to find out the RRC message type closely related to the current communication scenario and the corresponding parameter set; The configuration file generation unit is used to determine the accurate position, data type and applicable decoding algorithm information of each parameter in the RRC message based on the filtered parameter set, and to generate the decoding configuration file according to the preset format.

10. The method of claim 7, wherein, By analyzing and learning new rules to realize decoding, the compatibility of the system is improved, and the following steps are processed: The RRC message that cannot be correctly decoded is fully characterized; Then, the extracted features are compared with the stored RRC protocol rule library and other variant rules learned from history in detail, and the differences between the message and the existing rules are analyzed; Then, the decoding of the message is realized by adjusting the existing decoding parameters or learning new decoding rules; The process includes multiple trial decodings and result verifications of the message; Once an effective decoding method is found, the newly learned rules or parameter adjustments are recorded and updated to the RRC protocol rule library; At the same time, the new rule is fed back to the configuration generation module, so that the new message variant situation can be considered when generating the decoding configuration file in the future, thereby improving the decoding ability of the system to different RRC message variants.

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