Real-time visualization method and visualization system for radio frequency chip performance test

Abstract

The invention relates to the technical field of radio frequency chip performance testing, and particularly provides a real-time visualization method and visualization system for radio frequency chip performance testing, traditional single-thread sequence control is replaced by a multi-thread asynchronous acquisition architecture, and the testing efficiency is remarkably improved; through adding a timestamp label mechanism to each piece of test data, the cross-device data synchronization precision reaches a microsecond level, and the problem of asynchronous triggering of a radio frequency signal and direct current bias is solved. The radio frequency index data table constructed by automatic association realizes intelligent aggregation analysis of multiple parameters under multiple combinations, and avoids manual matching errors caused by data dispersed storage in a traditional scheme. Based on an automatic threshold setting and real-time judgment function of a test protocol, intelligent switching of judgment standards under a multi-protocol standard is supported, errors caused by manual configuration are reduced, and modification during protocol updating is avoided. And real-time visual rendering enables a user to dynamically observe a multi-parameter association change trend, so that the problem positioning efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of radio frequency chip performance testing technology, and in particular to a real-time visualization method and visualization system for radio frequency chip performance testing. Background Technology

[0002] Please refer to Figure 1 , Figure 1 This showcases an existing automated testing system for RF chips, primarily addressing issues related to automated equipment control, configuration management, and information acquisition and storage. The equipment control section mainly relies on single-threaded sequential control of test equipment (such as vector network analyzers, signal generators, spectrum analyzers, and power supplies) to collect and store S-parameters (such as S11 and S21), error vector magnitude (EVM), and adjacent channel leakage ratio (ACPR) according to a fixed procedure. While achieving unattended testing, the following technical bottlenecks remain:

[0003] Firstly, regarding data acquisition efficiency, traditional systems employ a single-threaded sequential acquisition architecture, requiring polling of each device to obtain test data. Taking the testing of a typical multi-band RF amplifier as an example, the single-threaded mode needs to sequentially acquire indicators such as DC bias, power, EVM, and ACPR, with a single test taking more than 30 seconds. This mode results in device idle waiting time, leading to insufficient test throughput and real-time performance.

[0004] Secondly, traditional solutions lack real-time visualization capabilities. Existing systems mostly output raw data files, such as CSV (Comma-Separated Values) or XLS (Data Management and Analysis) formats, or simple static charts. Users need to import the data into analysis tools, such as Excel (Microsoft Spreadsheet) or MATLAB (Matrix Labs), for secondary processing. They also need to manually write special scripts to complete data visualization and cannot observe the changes in the correlation of multiple parameters in real time, which reduces the efficiency of research and development debugging.

[0005] Furthermore, multi-threaded parallelism will cause timing errors. Traditional solutions generally have large timing errors in data synchronization accuracy, exceeding 100ms, which is unacceptable for RF chip testing that requires microsecond-level response.

[0006] Furthermore, traditional methods suffer from poor data correlation, with different test item data stored in separate files, such as scattered scan data for voltage, frequency, ACPR, and output power. This necessitates manual matching of multiple indicators under voltage-frequency-power combinations, making it difficult to discover deeper patterns such as the nonlinear correlation between ACPR and output power.

[0007] Finally, test data analysis is highly dependent on engineers' experience. Pre-set thresholds are required; for example, the criterion for EVM ≤ 3% needs to be manually configured. It cannot adapt to the differences in EVM requirements between multiple protocol standards, such as Wi-Fi 6E and 5G NR. When test specifications are updated, multiple judgment logics need to be modified, and the lack of dynamic baseline comparison functionality leads to low efficiency in version iteration testing. Summary of the Invention

[0008] This invention provides a real-time visualization method and system for radio frequency (RF) chip performance testing, which improves the testing efficiency and accuracy of RF chips and optimizes the entire process from data acquisition to analysis and presentation.

[0009] This invention provides a real-time visualization method for radio frequency chip performance testing, the method comprising:

[0010] Create multiple test control threads and bind a test device to each test control thread;

[0011] Multiple test control threads asynchronously control the corresponding test devices to perform RF chip performance testing;

[0012] After adding a timestamp tag to each of the collected test data, multiple test data sets are stored.

[0013] The test data are automatically correlated according to preset rules to construct a radio frequency index correlation data table;

[0014] Under the current test protocol, the judgment thresholds corresponding to each of the aforementioned radio frequency indicators are automatically set;

[0015] The radio frequency (RF) index is calculated in real time based on the test data in the RF index association data table, and it is determined in real time whether the RF index exceeds the judgment threshold.

[0016] If the radio frequency indicator does not exceed the judgment threshold, then the radio frequency indicator is visualized and rendered.

[0017] Furthermore, the test control thread includes:

[0018] The signal source control thread is used to acquire the voltage and current of the radio frequency chip;

[0019] An input power measurement thread is used to acquire the input power of the RF chip;

[0020] An output power measurement thread is used to acquire the output power of the RF chip;

[0021] An error vector amplitude measurement thread is used to acquire the error vector amplitude data of the radio frequency chip;

[0022] The adjacent channel leakage ratio measurement thread is used to collect adjacent channel leakage ratio data of the radio frequency chip.

[0023] Furthermore, after adding a timestamp tag to each of the collected test data, storing multiple sets of test data includes:

[0024] Add a microsecond-level timestamp tag to each of the test data in the order of collection;

[0025] Based on the microsecond-level timestamp tag, the different test data sets collected by different test control threads at the same test time are combined into a single synchronization dataset.

[0026] Furthermore, automatically associating multiple test data according to preset rules includes:

[0027] Aggregate test data with the same frequency and power combination in the synchronous dataset;

[0028] The data table is constructed according to the three dimensions of "frequency band-power-time";

[0029] Multi-parameter statistical analysis is performed using grouped aggregation functions.

[0030] Furthermore, under the current testing protocol, automatically setting the judgment thresholds corresponding to each of the aforementioned test data includes:

[0031] Under the current testing protocol, the automatic setting of judgment thresholds for each of the aforementioned test data includes:

[0032] Define the judgment thresholds and user-defined formulas for different test protocols in the configuration file;

[0033] Parse the pre-built protocol library and read the corresponding judgment threshold in the configuration file according to the current test protocol; or, directly configure the judgment threshold.

[0034] Based on the parsed judgment threshold, an upper and lower limit judgment matrix corresponding to the test protocol is generated;

[0035] The radio frequency indicators are determined in real time based on the upper and lower limit determination matrix.

[0036] Furthermore, the test protocols include Wi-Fi 6E, 5G NR, Wi-Fi 7, or 5G-Advanced.

[0037] Furthermore, the method also includes:

[0038] If the test data exceeds the judgment threshold, the test data is marked as abnormal.

[0039] Furthermore, the method also includes:

[0040] When the test data is updated, a signal-slot mechanism is used to immediately update the view and data of the visualization interface.

[0041] On the other hand, the present invention also provides a real-time visualization system for radio frequency chip performance testing, the system comprising:

[0042] Multiple thread control modules are configured to acquire test data from the RF chip;

[0043] An asynchronous control module is configured to control multiple test control threads to asynchronously control the corresponding test devices to perform RF chip performance testing.

[0044] A global data queue module is configured to collect the test data and add a timestamp tag to each test data.

[0045] The automatic association module is configured to automatically associate multiple test data according to preset rules;

[0046] The threshold setting module is configured to automatically set the judgment threshold corresponding to each of the test data.

[0047] The judgment module is configured to calculate the radio frequency index based on the radio frequency index association data table, and to determine in real time whether the test data exceeds the judgment threshold.

[0048] The visualization rendering module is configured to perform visualization rendering on the test data when the test data does not exceed the judgment threshold.

[0049] Furthermore, the visualization rendering module uses a signal-slot mechanism to update the test data in real time.

[0050] Furthermore, the visualization rendering module includes:

[0051] Interactive visualization analysis unit, including comparison sub-chart area and data table area;

[0052] The comparison sub-graph area is configured to perform multi-graph overlay comparison; the data table area updates and displays the radio frequency indicators in real time.

[0053] Furthermore, it also includes an anomaly tracing module;

[0054] The anomaly tracing module is configured to automatically trace the original record and display charts of other relevant indicators when a user interactively clicks on an anomaly data point.

[0055] Compared with the prior art, the present invention has at least the following technical effects:

[0056] This invention replaces traditional single-threaded sequential control with a multi-threaded asynchronous acquisition architecture, significantly improving testing efficiency. By adding timestamp tags to each test data point, cross-device data synchronization accuracy reaches the microsecond level, resolving the asynchronous triggering issue between RF signals and DC bias. The automatically constructed RF indicator data table enables intelligent aggregation analysis of multiple parameters under various combinations, avoiding manual matching errors caused by scattered data storage in traditional solutions. The automatic threshold setting and real-time judgment function based on the test protocol supports intelligent switching of judgment standards under multiple protocol standards, reducing manual configuration errors and avoiding modifications during protocol updates. Real-time visualization rendering allows users to dynamically observe the trends of multi-parameter correlation, improving the efficiency of problem localization compared to traditional offline data processing methods. Attached Figure Description

[0057] Figure 1 This refers to an automated testing system for radio frequency chips in the existing technology.

[0058] Figure 2 This is a simplified flowchart of the real-time visualization method for radio frequency chip performance testing in Embodiment 1 of the present invention;

[0059] Figure 3 This is a simplified flowchart of another method for real-time visualization of radio frequency chip performance testing in Embodiment 1 of the present invention;

[0060] Figure 4 This is a simplified flowchart illustrating the multi-threaded parallel acquisition process in Embodiment 1 of the present invention;

[0061] Figure 5 This is a simplified flowchart illustrating the upper and lower limit determination process in Embodiment 1 of the present invention;

[0062] Figure 6 This is a visual display diagram of the rendered image in Embodiment 1 of the present invention;

[0063] Figure 7 The trends of Gain, Eutra, LowEutraUp, and PAE with output power in Embodiment 2 of the present invention;

[0064] Figure 8 This is a schematic diagram obtained by superimposing three versions of Pout-PAE and Pout-EVM curves in the sub-graph area in Embodiment 2 of the present invention. Detailed Implementation

[0065] The following description, with reference to schematic diagrams, illustrates a real-time visualization method and system for radio frequency chip performance testing according to the present invention. Preferred embodiments of the invention are shown. It should be understood that those skilled in the art can modify the invention described herein while still achieving its advantageous effects. Therefore, the following description should be understood as being of general knowledge to those skilled in the art and is not intended to limit the invention.

[0066] The invention is described more specifically by way of example in the following paragraphs with reference to the accompanying drawings. The advantages and features of the invention will become clearer from the following description. It should be noted that the drawings are in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of the invention.

[0067] Example 1

[0068] Please refer to Figures 2-4 This embodiment provides a real-time visualization method for radio frequency chip performance testing, the method comprising:

[0069] S1. Create multiple test control threads and bind a test device to each test control thread;

[0070] S2. Multiple test control threads asynchronously control the corresponding test devices to perform RF chip performance testing;

[0071] S3. Store the collected test data and add a timestamp tag to each test data;

[0072] S4. Automatically associate multiple test data according to preset rules to construct a radio frequency index association data table;

[0073] S5. Under the current test protocol, automatically set the judgment threshold corresponding to each of the test data;

[0074] S6. Calculate the radio frequency index based on the test data in the radio frequency index association data table, and determine in real time whether the radio frequency index exceeds the judgment threshold;

[0075] S7. If the radio frequency indicator does not exceed the judgment threshold, then the radio frequency indicator is visualized and rendered.

[0076] In this embodiment, a multi-threaded asynchronous acquisition architecture replaces the traditional single-threaded sequential control, significantly improving testing efficiency. Adding timestamps to each test data point enables microsecond-level data synchronization across devices, resolving the asynchronous triggering issue between RF signals and DC bias. The automatically constructed RF performance data table enables intelligent aggregation and analysis of multiple parameters under various combinations, avoiding manual matching errors caused by scattered data storage in traditional solutions. Automatic threshold setting and real-time judgment functions based on the test protocol support intelligent switching of judgment standards across multiple protocol standards, reducing errors from manual configuration and avoiding modifications during protocol updates. Real-time visualization rendering allows users to dynamically observe the trends of multi-parameter correlation, improving the efficiency of problem localization compared to traditional offline data processing methods.

[0077] In one specific embodiment of step S1, multiple sub-threads are created based on the threading module of Python (an electronic programming technique), and the test control thread includes:

[0078] The system includes: a signal source control thread for acquiring the voltage and current of the RF chip; an input power measurement thread for acquiring the input power of the RF chip; an output power measurement thread for acquiring the output power of the RF chip; an error vector amplitude measurement thread for acquiring the error vector amplitude data of the RF chip; and an adjacent channel leakage ratio measurement thread for acquiring the adjacent channel leakage ratio data of the RF chip. Furthermore, those skilled in the art can select different test control threads according to actual needs, and no specific limitations are imposed here.

[0079] In one specific embodiment, the signal source control thread is equipped with a DC power acquisition device, the input power measurement thread is equipped with an input power meter acquisition device, the output power measurement thread is equipped with an output power meter acquisition device, and the error vector amplitude measurement thread and the adjacent channel leakage ratio measurement thread are equipped with a spectrum analyzer.

[0080] In a specific embodiment of step S2, the PyVISA (Control Test Instruments) library is used as the front-end of the virtual instrument software architecture in the Python environment to achieve stable communication with various test and measurement devices. This scheme standardizes control commands through the Standard Programmable Instrument Command (SCPI) protocol. Its core advantage lies in the fact that the system sends these SCPI commands asynchronously to multiple parallel test control threads, thereby achieving non-blocking device control and optimizing the acquisition cycle time.

[0081] A specific example of asynchronous transmission is as follows: an SCPI command for setting the carrier frequency and output power of the radio frequency signal source is asynchronously sent to the signal source control thread; at the same time, another command that triggers the input power reading can be sent to the input power measurement thread.

[0082] Furthermore, step S3, which stores the collected test data and adds a timestamp tag to each test data, includes:

[0083] S31. Add timestamp tags to each of the test data in the order of collection;

[0084] S32. Based on the timestamp tag, the different test data sets collected by different test control threads at the same test time are combined into a synchronization dataset.

[0085] Specifically, the purpose of S31-S32 is to ensure that when a test device in a certain thread completes its current task, the thread it occupies will be immediately released and put into the next task of the test sequence. For example, after the power meter in the input power measurement thread completes the input power test, it can switch to the next frequency band for testing within a set threshold.

[0086] In step S3, a brand-new multi-threaded testing architecture was built by combining dynamic scheduling, data queues, and high-precision timestamps. This architecture can reduce the device switching waiting time from 5 seconds to 0.5 seconds, greatly improving the testing speed. It can also achieve microsecond-level data synchronization, thereby capturing dynamic signals at the 10-microsecond level, solving the problem that traditional testing cannot solve.

[0087] Furthermore, the automatic association of multiple test data according to preset rules in step S4 includes:

[0088] S41. Correlate the test data with the same frequency and power combination within the synchronization dataset.

[0089] In a specific embodiment of S41, the DataFrame structure of Pandas (an open-source data analysis and manipulation tool library based on the Python programming language) is used to construct a data table according to the three dimensions of "frequency band-power-time", and multi-parameter aggregation (such as calculating the maximum value of ACPR in a certain frequency band, or the average current over a certain period of time) is achieved through the groupby function.

[0090] Furthermore, in step S5, under the current test protocol, automatically setting the judgment thresholds corresponding to each of the test data includes:

[0091] S51. Define the judgment thresholds and user-defined formulas for different test protocols in the configuration file;

[0092] S52. Parse the configuration file;

[0093] S53. Read the corresponding judgment threshold in the configuration file according to the current test protocol; or, directly configure the judgment threshold.

[0094] S54. Generate an upper and lower limit judgment matrix corresponding to the test protocol based on the parsed judgment threshold;

[0095] S55. Real-time determination of radio frequency indicators based on the upper and lower limit determination matrix.

[0096] In this embodiment, the configuration file is a predefined file that stores, for example, error vector amplitude (EVM) thresholds for different signal modulation methods (such as QPSK, 16QAM, and 64QAM), as well as other performance judgment criteria that may be related to the current test protocol. This file serves as the basis for automated judgment by the test system or device. The system parses it to obtain specific limit values ​​for judging whether the performance of the device under test is qualified under the current communication test protocol (e.g., LTE, 5G NR), and constructs an upper and lower limit matrix for automatic judgment based on these limit values.

[0097] In this embodiment, the testing protocol includes Wi-Fi 6E, 5G NR, Wi-Fi 7, or 5G-Advanced. Of course, those skilled in the art can choose different testing protocols according to actual circumstances, and no specific limitations are imposed here.

[0098] In step S5, the test criteria and program code are decoupled by configuring the judgment threshold in an external file. This greatly improves the flexibility and maintainability of the test system. When the test criteria change or are adapted to a new model, only the configuration file needs to be modified without altering the main program. This automated setting mechanism effectively avoids human configuration errors and significantly improves testing efficiency in large-scale production while ensuring the consistency and reliability of test results.

[0099] In one specific embodiment of step S53, the user can directly define the analysis formula as the upper and lower thresholds through an XML (Extensible Markup Language) configuration file, or set the upper and lower threshold values ​​according to a specific test protocol. The set upper and lower thresholds and their values ​​are not specifically limited here; those skilled in the art can set them according to different scenarios.

[0100] Furthermore, in a specific embodiment of step S6, which calculates the radio frequency (RF) metrics based on the test data in the RF metric association data table, the RF metrics include at least one of power dissipation and reverse coupling directivity parameters. Of course, those skilled in the art can calculate different RF metrics according to actual circumstances, and no specific limitations are imposed here.

[0101] The specific calculation method is as follows: The power dissipation P is calculated using a formula based on NumPy (a core library of the Python programming language). diss

[0102] P diss =V DC ×I DC -P RF ;

[0103] Among them, V DC For DC voltage, I DC To be converted to direct current; P RF = (np.power(10, ((Pout-30) / 10))-np.power(10, ((Pin-30) / 10))), where Pout is the output power, and Pin is the input power. RF It needs to be converted to W units for calculation.

[0104] Formulaic calculation of reverse coupling directionality parameters based on NumPy

[0105]

[0106] Wherein, S21 is the forward transmission coefficient, S22 is the output port reflection coefficient, S31 is the transmission coefficient from port 1 to port 3, and S33 is the reflection coefficient of port 3.

[0107] The above formula involves the calculation of multiple parameters. By collecting multiple S-parameters (S21 / S31 / S32, etc.), the formula is dynamically invoked. Real-time calculation of the reverse coupling directionality, followed by visualization, enables online user feedback, saving 90% of the time compared to traditional processing methods.

[0108] This invention comprises a multi-threaded data acquisition module and a dynamic data processing engine. The former addresses complex testing timing requirements by employing a dynamic thread scheduling algorithm and priority queues to ensure real-time acquisition of key parameters; the latter combines RF indicator calculation with multi-threaded data acquisition to achieve online fault diagnosis. Dynamic indicator calculation offers dual value: firstly, it achieves real-time calculation and feedback through zero-latency linkage, saving 90% of processing time; secondly, it can calculate voltage and current for multiple channels simultaneously, processing asynchronous data from multiple devices concurrently, completing complex RF indicator calculations such as power dissipation and directivity in one go, avoiding misinterpretation as routine mathematical operations. This solution solves the problem of asynchronous triggering of RF signals and DC bias, meeting microsecond-level testing requirements, and utilizes Pandas and NumPy for data cleaning, aggregation, and formulaic calculations.

[0109] Furthermore, in a specific embodiment of the visualization rendering in step S7, the visualization rendering object includes:

[0110] (1) Comparison sub-chart area: Embedded charts, supporting multiple chart overlays (such as comparison of the current test curve with historical data).

[0111] (2) Data table area: Displays detailed parameters under frequency band or power matrix.

[0112] Furthermore, when the test data is updated, a signal-slot mechanism is used to immediately update the view and data of the visualization interface.

[0113] As can be seen, with multiple data collections, the displayed data is also dynamically rendered. Through this update mechanism, users can more promptly and intuitively see performance trends, thus enabling them to make modifications to address specific issues.

[0114] Furthermore, to achieve effective data traceability and analysis, the system stores all test data in a structured format, based on test conditions, specific projects, and time periods, as a universal CSV file. This allows users to import and overlay multiple sets of historical data from different periods or batches with a single click. In the generated charts, each set of data can be assigned a unique color, line style (such as solid or dashed lines), and legend label for easy differentiation. This intuitive visualization and comparison method enables users to readily perform performance trend analysis, yield fluctuation tracing, and comparison of product versions, significantly improving the depth and efficiency of data analysis.

[0115] In summary, by employing the aforementioned real-time visualization method for RF chip performance testing, this invention achieves significant technological breakthroughs in accuracy, speed, and automation. It reduces cross-device data synchronization errors from the hundreds of milliseconds level to the sub-millisecond level, improving accuracy by over a hundredfold; simultaneously, it compresses a typical 25-minute test task to 4 minutes, increasing efficiency by 84%; and it replaces traditional manual configuration with a fully automated process. Overall, this invention effectively addresses the pain points of traditional testing—long testing time, low accuracy, and reliance on manual labor—significantly improving the overall efficiency and reliability of RF chip testing.

[0116] Example 2

[0117] This embodiment uses the real-time visualization method for RF chip performance testing described above. The testing method is as follows:

[0118] S100. Select the chip to be tested and the testing equipment;

[0119] S101. Selection of the chip under test;

[0120] Select a 5G RF amplifier chip that supports the n78 band (3.3-3.8GHz). This 5G RF amplifier chip has two input ports (RFIN1-RFIN2) and two output ports (RFOUT1-RFOUT2).

[0121] S102. Selection of Test Equipment:

[0122] (1) DC power supply: Supports multi-channel voltage scanning (range: 0.1-5V, step 0.1V);

[0123] (2) RF matrix switch: Supports 8×8 RF channel switching;

[0124] (3) Input power meter: Range: -30dBm to +20dBm;

[0125] (4) Output power meter: range: -20dBm to +30dBm;

[0126] (5) Signal source: Supports LTE and NR modulation signals;

[0127] (6) Temperature chamber: Supports temperature switching from -40° to 85°.

[0128] S200. Configure test parameters:

[0129] (1) The frequency points are 3.35GHz, 3.55GHz, and 3.75GHz;

[0130] (2) Input power range is -20dBm to +10dBm (in 1dBm steps);

[0131] (3) Output power range: 10dBm to 29dBm (this is the test limit range);

[0132] (4) The test signal is: DFT QPSK 100MHz 270RB (the signal processing method of this test signal is Discrete Fourier Transform, the data modulation scheme is Quadrature Phase Shift Keying, the signal width is 100 MHz and it actually occupies 270 resource blocks);

[0133] (5) The power supply voltage scan is: 3.2V, 3.4V, 4.3V;

[0134] (6) The test temperature is configured as -40°, 25° and 85°.

[0135] S300. Thread initialization and device binding:

[0136] (1) Thread 1 (RF signal source control thread): Responsible for generating high-precision RF excitation signals. It controls the signal source via Ethernet, outputting specified waveforms (e.g., DFT QPSK 100MHz 270RB), and can perform precise scanning in 1dB steps within a large frequency range (3.35GHz to 3.75GHz) and power range (-20dBm to +10dBm). The thread synchronously records the currently set frequency (Freq) and power (Psg) values.

[0137] (2) Thread 2 (DC Power Control Thread): Responsible for providing DC bias to the device under test. It sets the voltage of multiple channels via SCPI commands and acquires the actual voltage and current of each channel in real time at 0.1-second intervals (10 times the signal period). The product of the actual voltage and current is the instantaneous DC power consumption of the device, a key parameter for calculating efficiency.

[0138] (3) Thread 3 (RF matrix switch control thread): Switch the input and output port combination in a preset order (e.g., switch the first input terminal RFIN1 to the first RF output terminal RFOUT1, switch the first input terminal RFIN2 to the second output terminal RFOUT2, etc.), with a switching time ≤10ms, send a trigger signal to the signal source and power meter, and start the test synchronously.

[0139] (4) Thread 4 (Input Power Control Thread): Set the sampling frequency to 32 times the signal period of 10ms, and sample the power value 32 times within 0.32s. Read the data from the input power meter to obtain P. IN The testing system uses P IN Data is used to control the signal source to output a specified power P. SG .

[0140] (5) Thread 5 (Output Power Test Control Thread): Same real-time acquisition mode as input power, reads output power meter data, and calculates PA gain (Gain(dB) = P). OUT -P IN Regarding efficiency, it is necessary to convert Pout and Pin from dBm to W. The conversion method is as follows:

[0141]

[0142] (6) Thread 6 (Incubator Control Thread): Controls the test environment temperature, for example -40°C, and records the test temperature. Since the temperature change of the incubator is small, the acquisition period is set to 10 seconds for automatic acquisition.

[0143] (7) Thread 7 (DC bias MIPI (Mobile Industry Processor Interface) control and trigger thread): controls the chip to be in normal working static current and test port, and according to the data of the global data queue.

[0144] S400. Parallel Data Acquisition and Data Processing:

[0145] S401. Data Synchronization: Under each test condition, all threads collect data with timestamps. Due to differences in real-time performance and importance, the data is placed in a global data queue. By comparing the timestamps, a 1ms error difference is designed to synchronize the data collected by all threads under the current test condition. When all data collection is complete, multi-threaded collection for the next test condition immediately begins.

[0146] S402. Anomaly Detection: If, at a certain voltage point and temperature, the user-defined Gain is less than...

[0147] 10dBm. The GUI automatically marks the data as having too low a gain in red, skips this test item, and continues with subsequent tests.

[0148] S403. Real-time visualization output: When the data collection queue receives data, it immediately performs data cleaning and real-time visualization output, which consists of two parts: comparison sub-graphs and data tables.

[0149] S404. Output comparative dynamic charts and data tables: Please refer to... Figure 7 The chart displays the trends of Gain, Eutra (parameters of the radio portion in LTE mobile communication systems), LowEutraUp (operating parameters of the LTE uplink in low-frequency bands), and PAE (Power Added Efficiency) as a function of output power. For different test conditions, such as 3.2V / 3.4V / 4.3V, multiple curves are compared, distinguished by color. Please refer to Table 1, which shows the key performance parameters of the RF amplifier when the output power is fixed at 28dBm.

[0150] Table 1

[0151]

[0152] Example 3

[0153] This embodiment uses the real-time visualization method for RF chip performance testing described above. The testing method is as follows:

[0154] S1000. Select the chip under test, which includes the initial configuration version of the WIFI7 PA (radio frequency amplifier) ​​chip wafer, the WIFI7 PA chip wafer with optimized linearity EVM, and the WIFI7 PA chip wafer with improved high-frequency stability.

[0155] S1000 Configuration Test Parameters:

[0156] (1) Signal source: Various signals are generated according to the 802.11BE protocol. The signal frame lengths are 0.5ms, 1ms, 2ms, and 4ms. The duty cycles are 10%, 50%, and 90% (high load), respectively. The modulation parameters are 4096QAM, the subcarrier spacing is 78.125kHz, and the bandwidth is 160MHz.

[0157] (2) Input / output power meter: records dynamic input power (P) IN ) and output power (P) OUT ).

[0158] (3) DC power supply: scanning voltage is 3.4V and 5V.

[0159] (4) Data storage: All test data is stored in CSV format according to version number (fields: timestamp, voltage Vcc, frequency Freq, signal name, signal frame length, signal duty cycle, input power P). IN Output power P OUT Gain, EVM, PAE, and current.

[0160] S2000. Thread initialization and device binding:

[0161] (1) Thread 1 (Signal Control): Send a 160M 4096QAM signal to the PA input, set the frequency test points to 5150MHz, 5500MHz, and 5850MHz, and the power range to -30dBm to 0dBm. Test the signal frame length (0.28ms, 1ms) and various duty cycles (10%, 50%, 90%) in sequence.

[0162] (2) Thread 2 (Power Control): Adjust the power supply voltage in steps and record the current value synchronously (for PAE calculation).

[0163] (3) Thread 3 (Power Meter Control): Reads the real-time input and output power, and calculates PAE and Gain.

[0164] (4) Thread 4 (Spectrum Analyzer Control): Controls the spectrum analyzer to set parameters such as frequency, bandwidth, frame length and duty cycle of the signal. The spectrum analyzer captures the EVM value and ends the current test condition according to the user definition, such as EVM>=3%.

[0165] The S3000 parallel data acquisition and processing was tested using the method disclosed in Example 1. Data from the three chip versions was tested and saved using a CSV file.

[0166] S4000. Outputs comparative dynamic charts and data tables:

[0167] Test data is displayed in real-time via a GUI interface, including dynamic charts and data tables. The dynamic charts include multiple comparison sub-charts, and the data tables include a real-time display of test data. The comparison sub-charts show the changes in Power Efficiency (PAE) and Power VVM with output power. For test anomalies or failures of undefined items (e.g., gain ripple greater than 3dB), users can quickly stop testing that version and continue optimizing other versions.

[0168] S5000 Historical Data Loading and Interactive Analysis:

[0169] S5001. Data Callback: Users load all historical test CSV data for the three versions of the chip mentioned above through the GUI interface. The system will automatically parse and construct a multi-subgraph analysis view and table values. The table values ​​are displayed as follows:

[0170] Table 2

[0171]

[0172]

[0173] S5002. Interactive Analysis:

[0174] (1) Please refer to Figure 8 By overlaying three versions of the Pout-PAE (output power-power-added efficiency curve) and Pout-EVM (output power-error vector amplitude curve) curves in the comparison sub-plot area of ​​the GUI interface, the differences in linearity and efficiency between the different versions are clearly visualized. Users can zoom in and out on specific areas of the data.

[0175] (2) The system automatically hides test data and curves that do not meet the requirements when the user inputs constraints. Alternatively, the system can specify the characteristic parameters of the initial version of the WIFI7 PA chip to study its basic performance, and then empirically evaluate the WIFI7 PA chip after optimizing linearity EVM and the WIFI7 PA chip with improved high-frequency stability.

[0176] (3) Users can sort the data in the master table by any performance metric (such as EVM) to quickly locate the worst-performing or abnormal data points. Selecting these rows will automatically highlight their corresponding curves in all relevant visualization subplots, enabling rapid problem localization from tables to graphs. Conversely, users can also directly select a test curve of interest in any subplot, and the system will automatically locate and highlight its corresponding entry in the master table and its associated curves in all other subplots. Furthermore, the system supports an isolated display function, which can temporarily hide other data, allowing users to focus on specific curves for in-depth analysis.

[0177] Example 4

[0178] This embodiment provides a real-time visualization system for radio frequency (RF) chip performance testing, implementing the real-time visualization method for RF chip performance testing disclosed in Embodiment 1. The system includes:

[0179] Multiple thread control modules are configured to acquire test data from the radio frequency chip.

[0180] The asynchronous control module is configured to control multiple test control threads to asynchronously control the corresponding test devices to perform RF chip performance testing.

[0181] The global data queue module is configured to collect the test data and add a timestamp tag to each test data.

[0182] The automatic association module is configured to automatically associate multiple test data according to preset rules.

[0183] The threshold setting module is configured to automatically set the threshold corresponding to each test data.

[0184] The judgment module is configured to calculate the radio frequency index based on the radio frequency index association data table, and to determine in real time whether the test data exceeds the judgment threshold.

[0185] The visualization rendering module is configured to perform visualization rendering on the test data.

[0186] Furthermore, the visualization rendering module uses a signal-slot mechanism to update the test data in real time.

[0187] Furthermore, the visualization rendering module includes:

[0188] Interactive visualization analysis unit, including comparison sub-chart area and data table area;

[0189] The comparison sub-image area is configured to enable multi-image overlay comparison.

[0190] Furthermore, it also includes an anomaly tracing module;

[0191] The anomaly tracing module is configured to automatically trace the original record and display charts of other relevant indicators when a user interactively clicks on an anomaly data point.

[0192] The technical effects achieved by the above-mentioned real-time visualization system for RF chip performance testing are the same as those achieved by the real-time visualization method for RF chip performance testing in Example 1, and will not be repeated here.

[0193] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A real-time visualization method for radio frequency chip performance testing, characterized in that, The method includes: Create multiple test control threads and bind a test device to each test control thread; Multiple test control threads asynchronously control the corresponding test devices to perform RF chip performance testing; After adding a timestamp tag to each of the collected test data, multiple test data sets are stored. The test data are automatically correlated according to preset rules to construct a radio frequency index correlation data table; Under the current test protocol, the judgment thresholds corresponding to each of the aforementioned radio frequency indicators are automatically set; The radio frequency (RF) index is calculated in real time based on the test data in the RF index association data table, and it is determined in real time whether the RF index exceeds the judgment threshold. If the radio frequency indicator does not exceed the judgment threshold, then the radio frequency indicator is visualized and rendered.

2. The real-time visualization method for RF chip performance testing as described in claim 1, characterized in that, The test control thread includes: The signal source control thread is used to acquire the voltage and current of the radio frequency chip; An input power measurement thread is used to acquire the input power of the RF chip; An output power measurement thread is used to acquire the output power of the RF chip; An error vector amplitude measurement thread is used to acquire the error vector amplitude data of the radio frequency chip; The adjacent channel leakage ratio measurement thread is used to collect adjacent channel leakage ratio data of the radio frequency chip.

3. The real-time visualization method for RF chip performance testing according to claim 1, characterized in that, After adding a timestamp tag to each of the collected test data, storing multiple sets of test data includes: Add a microsecond-level timestamp tag to each of the test data in the order of collection; Based on the microsecond-level timestamp tag, the different test data sets collected by different test control threads at the same test time are combined into a single synchronization dataset.

4. The real-time visualization method for RF chip performance testing according to claim 3, characterized in that, Automatic association of multiple test data according to preset rules includes: Aggregate test data with the same frequency and power combination in the synchronous dataset; The data table is constructed according to the three dimensions of "frequency band-power-time"; Multi-parameter statistical analysis is performed using grouped aggregation functions.

5. The real-time visualization method for RF chip performance testing according to claim 1, characterized in that, Under the current testing protocol, automatically setting the judgment thresholds corresponding to each of the aforementioned test data includes: Define the judgment thresholds and user-defined formulas for different test protocols in the configuration file; Parse the pre-built protocol library and read the corresponding judgment threshold in the configuration file according to the current test protocol; or, directly configure the judgment threshold. Based on the parsed judgment threshold, an upper and lower limit judgment matrix corresponding to the test protocol is generated; The radio frequency indicators are determined in real time based on the upper and lower limit determination matrix.

6. The real-time visualization method for RF chip performance testing according to claim 1, characterized in that, The testing protocols include Wi-Fi 6E, 5G NR, Wi-Fi 7, or 5G-Advanced.

7. The real-time visualization method for RF chip performance testing according to claim 1, characterized in that, The method further includes: If the test data exceeds the judgment threshold, the test data is marked as abnormal.

8. The real-time visualization method for RF chip performance testing according to claim 1, characterized in that, The method further includes: When the test data is updated, a signal-slot mechanism is used to immediately update the view and data of the visualization interface.

9. A real-time visualization system for testing the performance of radio frequency chips, characterized in that, The system includes: Multiple thread control modules are configured to acquire test data from the RF chip; An asynchronous control module is configured to control multiple test control threads to asynchronously control the corresponding test devices to perform RF chip performance testing. A global data queue module is configured to collect the test data and add a timestamp tag to each test data. The automatic association module is configured to automatically associate multiple test data according to preset rules; The threshold setting module is configured to automatically set the judgment threshold corresponding to each of the test data. The judgment module is configured to calculate the radio frequency index based on the radio frequency index association data table, and to determine in real time whether the test data exceeds the judgment threshold. The rendering module is configured to perform visual rendering of the test data when the test data does not exceed the judgment threshold.

10. The real-time visualization system for RF chip performance testing according to claim 9, characterized in that, The visualization rendering module uses a signal slot mechanism to update the test data in real time.

11. The real-time visualization system for RF chip performance testing according to claim 9, characterized in that, The visualization rendering module includes: Interactive visualization analysis unit, including comparison sub-chart area and data table area; The comparison sub-image area is configured to perform multi-image overlay comparison; the data table area updates and displays the radio frequency indicators in real time.

12. The real-time visualization system for RF chip performance testing according to claim 9, characterized in that, It also includes an anomaly tracing module; The anomaly tracing module is configured to automatically trace the original record and display charts of other relevant indicators when a user interactively clicks on an anomaly data point.

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