Protocol-aware 5G O-RAN component automatic test method and system

Abstract

The invention provides a 5G O-RAN component automatic test method and system based on protocol perception. The method comprises the following steps: firstly, based on an O-RAN normative document protocol, extracting functional definition information, participating entities and communication interface information of a target component, and generating an expected signaling process in combination with a retrieval enhancement generation technology and a large language model; then, based on the communication test case in the expected signaling process, executing a communication test on the to-be-tested O-RAN component, and obtaining an actually executed standard communication process through network flow collection and protocol analysis; and finally, comparing and analyzing the standard communication process and an expected signaling process, and outputting test results including signaling sequence abnormity, message missing and message errors. According to the invention, automatic testing of the communication behavior of the O-RAN component is realized, manual intervention is reduced, the testing efficiency and accuracy are improved, the interoperability verification capability among multi-manufacturer components is enhanced, and the communication reliability and stability of a 5G O-RAN system are improved.

Description

Technical Field

[0001] This invention relates to the field of 5G communication, and more particularly to the testing of the Open Radio Access Networks (O-RAN) standard. Specifically, it targets the functional testing, interoperability testing, and security testing of communication between various components of the 5G O-RAN network. By extracting the behavioral and functional requirements of various components defined in the document specifications and converting them into the expected communication flow between components, and then recording the actual communication process and comparing it with the corresponding expected communication flow, automated 5G O-RAN component testing is achieved. Background Technology

[0002] O-RAN (Open Radio Access Network) is a new RAN architecture based on open interfaces, hardware and software decoupling, and network intelligence. Its core lies in enabling interoperability of equipment from multiple vendors through standardized interfaces (such as Open Fronthaul, A1, E2, etc.) and migrating the functions of traditional dedicated hardware to a general platform with the help of cloud and virtualization technologies, thereby improving the flexibility, scalability and cost efficiency of the network. At the same time, it introduces RAN Intelligent Controller (RIC) to support AI / ML-based network optimization and automated operation and maintenance.

[0003] According to the definitions of the various working groups of O-RAN ALLIANCE (especially WG4, WG5 and WG11), O-RAN testing is a comprehensive system that covers conformance testing, interoperability testing and end-to-end / system testing. It aims to verify the compatibility of equipment from different vendors on open interfaces, the compliance of protocol implementations, and the performance and stability of multi-component integration, thereby ensuring the reliability and commercial viability of network deployment in an open ecosystem.

[0004] Current O-RAN testing methods still have several limitations, including complex testing environments that are difficult to reproduce real network scenarios, test combination explosion caused by multi-vendor combinations, test case lag due to frequent interface specification evolution, and lack of unified evaluation standards and repeatable verification mechanisms in AI / ML-driven RIC application scenarios. These factors together limit testing efficiency, coverage, and comparability of results. Summary of the Invention

[0005] This invention proposes a specification-aware automated testing method and system for 5G O-RAN components, providing automated testing support for the communication reliability between 5G O-RAN components from different manufacturers. The invention first utilizes existing O-RAN documentation specifications as a reference, extracting the functional definitions of O-RAN components. Then, using the constraints of the specifications and a large language model, it generates specific expected signaling flows. These expected signaling flows are then compared with signaling flows captured during actual communication, achieving automated testing of specific functions. This method and system overcome the shortcomings of traditional 5G O-RAN component testing, which relies on manual testing and verification, improving testing efficiency and accuracy, and ensuring the communication reliability of 5G O-RAN components.

[0006] The method of the present invention specifically includes the following steps:

[0007] Step 1: Generation of the expected signaling flow based on the document specification. This includes four sub-steps:

[0008] Step 1.1: Use natural language processing methods (such as analysis based on large language models) to extract the functional definition description text of specific communication components from existing O-RAN specification documents, including functional descriptions and information required for function execution.

[0009] Step 1.2: Extract the participating entities, communication interfaces, and protocol context information from the description text obtained in Step 1.1.

[0010] Step 1.3: Using the large language model Retrieval-Augmented Generation technique, the information from Step 1.2 is used as keywords to search for relevant test cases in existing O-RAN specification documents.

[0011] Step 1.4: Using the information extracted in Step 1.1 and the search results in Step 1.4, call the large language model to synthesize an expected signaling flow, which includes communication test cases and expected execution results.

[0012] Step 2: Extract standard communication flow based on network traffic capture. This includes three sub-steps:

[0013] Step 2.1: Use the communication test cases contained in the expected signaling flow generated in Step 1 to test the O-RAN component to be tested.

[0014] Step 2.2: Use a network traffic logging tool to capture the network traffic from Step 2.1.

[0015] Step 2.3: Use a protocol analysis tool to convert the binary network traffic data captured in Step 2.2 into text format, representing the actual standard communication process executed.

[0016] Step 3: Automated testing based on communication flow comparison. This includes four sub-steps:

[0017] Step 3.1: Compare the standard communication flow generated in Step 2 with the expected signaling flow generated in Step 1 to verify whether the signaling order is consistent. If the order is inconsistent, mark it as "message order error".

[0018] Step 3.2: If a specific message appears in the expected signaling flow but does not exist in the standard communication flow, it is marked as "message missing".

[0019] Step 3.3: If a specific message appears in the standard communication flow but does not exist in the expected signaling flow, it is marked as "message error".

[0020] Step 3.4: Output the results of steps 3.1-3.3 as test results.

[0021] Based on the above steps, the present invention proposes a specification-aware 5G O-RAN component automated testing system, comprising the following components: 1) a document specification analysis and extraction unit, used to analyze existing O-RAN specification documents and output expected signaling flow; 2) a network recording unit, used to drive O-RAN components to execute test cases and capture their network traffic to form a standard communication flow; 3) a test result comparison unit, used to analyze the differences between the expected signaling flow and the standard communication flow and form test conclusions. Technical effect

[0022] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0023] First, it automates the testing process, reduces manual intervention, and improves testing efficiency.

[0024] Second, based on the specifications, test criteria are generated to improve the accuracy and consistency of testing, support the dynamic generation of test cases, expand test coverage, and enhance the interoperability verification capabilities between components from multiple vendors.

[0025] Third, it can detect signaling loss, errors and sequence anomalies in the communication process, improve the ability to locate problems, enhance the reliability and stability of 5G O-RAN system communication, and is suitable for complex network environments and intelligent scenarios, with good scalability. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of a protocol-aware 5G O-RAN component automated testing method disclosed in an embodiment of the present invention.

[0027] Figure 2 This is a schematic diagram of an automated testing system architecture for a specification-aware 5G O-RAN component disclosed in an embodiment of the present invention. Detailed Implementation

[0028] This embodiment provides an automated testing method for 5G O-RAN components. By parsing O-RAN specification documents, a desired signaling flow is generated and compared with the actual communication flow to achieve automated verification of the communication behavior of the target component. This method can be applied to interface testing scenarios between different components (such as O-CU, O-DU, RIC, etc.) in the O-RAN system, such as functional testing and interoperability testing of E2 or A1 interfaces.

[0029] Step S1: Expected signaling flow generation. In this embodiment, firstly, the O-RAN specification document (e.g., the interface specification document published by WG4, WG5, or WG11) is obtained. For the target test function (e.g., the subscription and control flow in the E2 interface), the following processing is performed:

[0030] Information extraction: Extract functional description text related to the target function from the specification document, including: function definition (e.g., E2 Subscription procedure), communication entities involved (e.g., Near-RT RIC and O-DU), interface type (e.g., E2 interface), and protocol context (e.g., E2AP protocol message).

[0031] Structured parsing: Semantic parsing of the text to identify message interaction order, message type (request / response / instruction, etc.), necessary parameters and constraints.

[0032] Test case retrieval: Based on the Retrieval Enhancement Generation (RAG) method, historical test cases related to the target function are retrieved from the existing O-RAN test case library or specification documents to supplement contextual information.

[0033] Expected Signaling Flow Generation: The extracted information and retrieval results are input into the large language model, which generates a standardized expected signaling flow. The expected signaling flow includes a complete signaling interaction sequence, the sender and receiver of each signaling step, and the expected response result.

[0034] Step S2: Obtaining the Standard Communication Flow. Based on the expected signaling flow generated in Step S1, the O-RAN component to be tested is actually tested, and the standard communication flow is formed according to the following procedure:

[0035] Test execution: Drive the component under test to run using test cases defined in the expected signaling flow, such as sending a subscription request from the RIC simulator to the O-DU.

[0036] Network traffic collection: During the communication process, network packet capture tools (such as tcpdump or Wireshark) are used to capture interface communication data in real time to obtain raw binary data.

[0037] Protocol parsing: The captured data is parsed using protocol parsing tools, converting it from binary format to readable text format, and extracting the actual signaling sequence, message type, and parameters.

[0038] Step S3: Communication Flow Comparison and Test Analysis. In this embodiment, the expected signaling flow generated in step S1 is compared and analyzed with the standard communication flow obtained in step S2, and the following process is followed:

[0039] Sequence consistency judgment: Compare the signaling order of the two to determine if there is a sequence deviation. If the signaling order is inconsistent, it is marked as "sequence abnormal".

[0040] Anomaly detection: If a signaling message exists in the expected process but does not exist in the actual process, it is marked as "Message Missing"; if a signaling message exists in the actual process but does not exist in the expected process, it is marked as "Message Error".

[0041] Output results: Summarize the above test results and generate a test report. The test report includes 1) test pass / fail conclusion, 2) anomaly type and corresponding signaling location, and 3) problem description information analysis.

[0042] In this embodiment, corresponding to the above method steps, the system can be specifically implemented as follows: 1) Document specification analysis and extraction unit: used to parse O-RAN specification documents and extract functional information; 2) Expected signaling generation unit: used to generate expected signaling flow by combining retrieval enhancement generation technology and large language model; 3) Network traffic acquisition unit: used to capture network data during communication; 4) Protocol parsing unit: used to parse network data into structured signaling flow; 5) Flow comparison and analysis unit: used to perform flow comparison and anomaly detection; 6) Test result output unit: used to generate test report.

[0043] The above units can be deployed on the same server or deployed in a distributed manner on multiple nodes.

[0044] The method described in this embodiment can automatically generate test procedures that conform to specifications, automatically acquire actual communication processes, and automatically identify communication anomalies, thereby achieving efficient, accurate, and scalable automated testing of O-RAN components.

[0045] The above-described specific implementations can be partially adjusted by those skilled in the art in different ways without departing from the principles and purpose of the present invention. The scope of protection of the present invention is defined by the claims and is not limited to the above-described specific implementations. All implementation schemes within the scope of the claims are bound by the present invention.

Claims

1. A protocol-aware automated testing method for 5G O-RAN components, characterized in that, The process includes the following steps: S1. Generating the expected signaling flow based on the O-RAN specification document, including: extracting the functional definition description information of the target O-RAN component from the specification document, obtaining the entities, communication interfaces, and protocol context information involved in the communication, and generating the corresponding expected signaling flow based on the information; S2. Obtaining the standard communication flow, including: performing communication tests on the O-RAN component to be tested based on the communication test cases in the expected signaling flow, and capturing and parsing the network traffic during the communication process to obtain the actually executed standard communication flow; S3. Performing a communication flow comparison analysis, including: comparing the standard communication flow with the expected signaling flow, and outputting test results based on the comparison results.

2. The protocol-aware automated testing method for 5G O-RAN components according to claim 1, characterized in that, The specific steps in step S1 for generating the expected signaling flow include: S1.1 Extracting the function description text related to the target function and the information required for function execution from the O-RAN specification document; S1.2 Extracting the participating entities, communication interfaces, and protocol context information from the function description text; S1.3 Retrieving relevant communication test cases from existing O-RAN specification documents based on the retrieval enhancement generation method; S1.4 Generating the expected signaling flow by calling the large language model based on the extracted information and retrieval results.

3. The protocol-aware automated testing method for 5G O-RAN components according to claims 1 to 2, further characterized in that, Obtaining the standard communication process specifically includes: 1) using the communication test cases in the expected signaling process to drive the O-RAN component under test to execute the communication process; 2) capturing network traffic during the communication process using a network traffic recording tool; and 3) using a protocol analysis tool to parse the captured network traffic into text format to form a standard communication process.

4. The protocol-aware automated testing method for 5G O-RAN components according to claims 1 to 3, further characterized in that, The communication process comparative analysis specifically includes: comparing the signaling order in the standard communication process and the expected signaling process; when the signaling order is inconsistent, it is marked as an abnormal signaling order; when there is a signaling in the expected signaling process but not in the standard communication process, it is marked as a missing message; when there is a signaling in the standard communication process but not in the expected signaling process, it is marked as a message error.

5. A protocol-aware automated testing system for 5G O-RAN components, characterized in that, include: 1) Document specification analysis and extraction unit, used to extract functional definition information and communication-related information of target components from O-RAN normative document specifications; 2) Expected signaling generation unit, used to generate expected signaling flow based on the functional definition information; 3) Network traffic acquisition unit, used to capture network traffic during communication when the O-RAN component under test is subjected to communication testing; 4) Protocol parsing unit, used to parse the network traffic to generate standard communication procedures; 5) Process comparison and analysis unit, used to compare and analyze the standard communication process with the expected signaling process; 6) Test result output unit, used to output test results based on the comparison and analysis results.

6. The binary code analysis system for cross-architecture knowledge transfer according to claim 5, further characterized in that, The expected signaling generation unit includes: 1) an information extraction subunit, used to extract participating entities, communication interfaces and protocol context information; 2) a test case retrieval subunit, used to retrieve relevant communication test cases based on the retrieval enhancement generation method; and 3) a signaling generation subunit, used to call the large language model to generate the expected signaling flow.

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