Edge-integrated vehicle-mounted 5G communication module and use method thereof

Abstract

The invention relates to the technical field of edge-integrated vehicle-mounted 5G communication modules, in particular to an edge-integrated vehicle-mounted 5G communication module and a use method thereof.The edge-integrated vehicle-mounted 5G communication module comprises a 5G communication sub-module, an edge calculation sub-module, a vehicle-mounted data and control interface sub-module, a safety and system management sub-module and a power management and physical bearing sub-module; wherein the 5G communication sub-module comprises a 5G baseband processing unit used for completing stable communication access in a vehicle-mounted environment, a radio frequency transceiving unit, a radio frequency front end and antenna interface unit, a network access and protocol control unit and a radio frequency power and temperature management unit; the radio frequency transmit-receive unit comprises a radio frequency calibration and compensation system, and the system comprises a temperature sensor which is arranged near a radio frequency front end and is used for collecting an environment temperature signal. According to the invention, the communication stability, the long-term reliability and the device service life of the vehicle-mounted 5G communication module in a complex temperature and high-load scene are improved.

Description

Technical Field

[0001] This invention relates to an integrated edge vehicle-mounted 5G communication module and its usage method, belonging to the technical field of integrated edge vehicle-mounted 5G communication modules. Background Technology

[0002] With the development of vehicle intelligence and vehicle-road cooperative applications, vehicle-mounted 5G communication modules need to work for a long time in the complex and drastically changing temperature environment inside the vehicle, and ensure the stability and reliability of the link in high transient transmission power scenarios (such as uplink burst services, V2X broadcast, and remote transmission of large amounts of video).

[0003] In current engineering practice, the methods commonly used to compensate for the effects of temperature on the performance of radio frequency devices (especially power amplifiers (PAs), low-noise amplifiers (LNAs), local oscillators, etc.) are:

[0004] Temperature sensors are placed near key components of the radio frequency front end to collect the temperature of the casing or PCB in real time;

[0005] Based on the temperature-RF parameter mapping table (or interval table) obtained from factory calibration or experimental calibration, the measured temperature is used as the input of the mapping table to adjust parameters such as PA bias, transmit power limit, LNA bias or baseband IQ correction;

[0006] Existing technologies typically compensate by placing temperature sensors near RF front-end devices and using a pre-established temperature-RF parameter mapping table. However, due to spatial discrepancies between the temperature measured by the sensors and the actual junction temperature of the RF devices, and the rapid rise in junction temperature and sensor response lag in high-power burst service scenarios, the compensation action becomes delayed or inaccurate. Furthermore, the mapping table is susceptible to failure due to device aging and long-term operating condition changes, leading to problems such as increased instantaneous bit error rate, unstable transmit power, and decreased reliability. Therefore, there is an urgent need to improve an integrated edge-mounted 5G communication module for vehicles and its usage method to solve the aforementioned problems. Summary of the Invention

[0007] The purpose of this invention is to provide an integrated edge vehicle-mounted 5G communication module and its usage method, in order to solve the problems of existing technologies that typically use temperature sensors deployed near radio frequency front-end devices and compensated according to a pre-established temperature-RF parameter mapping table. However, due to the spatial deviation between the temperature measured by the sensor and the actual junction temperature of the radio frequency device, and the rapid rise of junction temperature and the lag in sensor response under high-power burst service scenarios, the compensation action is delayed or inaccurate. At the same time, the mapping table is also susceptible to device aging and long-term operating condition changes, which can gradually become invalid, thereby causing problems such as increased instantaneous bit error rate, unstable transmission power and decreased reliability.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] An integrated edge computing vehicle-mounted 5G communication module and its usage method are disclosed, comprising a 5G communication submodule, an edge computing submodule, a vehicle-mounted data and control interface submodule, a security and system management submodule, and a power management and physical bearer submodule. The 5G communication submodule includes a 5G baseband processing unit, a radio frequency transceiver unit, a radio frequency front-end and antenna interface unit, a network access and protocol control unit, and a radio frequency power and temperature management unit for achieving stable communication access in a vehicle environment.

[0010] The radio frequency transceiver unit includes a radio frequency calibration and compensation system, the system comprising:

[0011] A temperature sensor is placed near the radio frequency front end to collect ambient temperature signals;

[0012] The radio frequency (RF) operating status acquisition unit is used to acquire the real-time power of RF devices. and launch duty cycle Operating status parameters;

[0013] Storage unit for storing the equivalent thermal resistance of the radio frequency device. and equivalent heat capacity ;

[0014] The junction temperature dynamic estimation unit, based on the temperature collected by the temperature sensor, the RF operating status parameters, and the equivalent thermal resistance and equivalent thermal capacity, estimates the junction temperature of the RF device according to a discrete recursive relationship. Perform estimation to obtain the junction temperature estimate. ;

[0015] The mapping and compensation unit obtains the corresponding RF compensation parameters from the pre-stored junction temperature-RF parameter mapping table based on the estimated junction temperature value and outputs them to adjust the power amplifier bias, LNA bias, local oscillator frequency compensation, or digital baseband IQ correction parameters of the RF front end.

[0016] Furthermore, the junction temperature dynamic estimation unit adopts a discrete recursive model:

[0017]

[0018] In the formula, For the first sample The estimated junction temperature at time [time]. For the first Temperature sensor reading at the sampling time and To and , And coefficients related to the sampling period.

[0019] Furthermore, the junction temperature dynamic estimation unit further includes a transient temperature rise prediction subunit, used to detect the RF power. During a rapid rise event, the feedforward prediction term is calculated based on the power change rate. And this prediction term is superimposed on the estimated junction temperature, that is:

[0020]

[0021] in, These are calibration coefficients used to achieve feedforward prediction and compensation for transient junction temperature rise caused by sudden launches.

[0022] Furthermore, it also includes a radio frequency performance feedback acquisition unit for periodically or on-demand acquisition of link performance indicators, including but not limited to: bit error rate, error vector magnitude, received signal strength indication, or uplink / downlink throughput; and a model self-correction unit for adjusting the equivalent thermal resistance based on the deviation between the link performance indicators and the desired performance. With equivalent heat capacity or , The coefficients are updated slowly using timescales or calibration corrections to adapt to device aging or long-term environmental changes.

[0023] Furthermore, the junction temperature-RF parameter mapping table used by the mapping and compensation unit includes at least: power amplifier bias voltage / current settings, transmit power limits, LNA bias settings, local oscillator frequency deviation compensation amounts, and baseband IQ correction coefficients corresponding to different junction temperature ranges; and the mapping table supports range switching or interpolation calculation based on the estimated junction temperature value to generate specific compensation parameters.

[0024] Furthermore, the system also includes multiple temperature sensors, which are respectively deployed near different key radio frequency components and near the module end. The junction temperature dynamic estimation unit determines the ambient temperature based on the temperature data from the multiple temperature sensors using a weighted fusion or nearest neighbor selection method. .

[0025] Furthermore, in the discrete recursive model of the junction temperature dynamic estimation unit, and The specific values ​​are determined by the following relationship:

[0026] , ;

[0027] in, The sampling period is the sampling period, and the and It is stored in the storage unit after factory calibration.

[0028] Furthermore, it also includes a fault detection and protection unit, which generates an over-temperature alarm and triggers the mapping and compensation unit to perform derating control or limit transmission power protection actions when the junction temperature estimate or the temperature sensor reading exceeds a preset threshold, so as to protect the radio frequency device from damage.

[0029] Furthermore, it includes the following steps:

[0030] Step 1: Collect the temperature near the RF front end using a temperature sensor. ;

[0031] Step 2: Acquire the real-time power of the RF device and duty cycle Operating status parameters;

[0032] Step 3: Based on the data described in Steps 1-2 and the known equivalent thermal resistance With equivalent heat capacity Calculate the estimated junction temperature of the RF device according to the discrete recursive relationship. :

[0033]

[0034] In the formula, , and , Sampling period Related;

[0035] Step 4: Upon detection During rapid increases, the prediction term is calculated based on the rate of power change and then... Feedforward correction is obtained ;

[0036] Step 5: Based on the junction temperature estimate from Step 3 or Step 4, obtain the RF compensation parameters from the junction temperature-RF parameter mapping table and perform corresponding parameter adjustments on the RF front end;

[0037] Step 6: Periodically or on-demand adjust based on link performance feedback and Update slowly.

[0038] Further, in step 4, the prediction term The calculation formula is:

[0039] ;

[0040] In the formula, These are the coefficients determined through calibration.

[0041] This invention has at least the following beneficial effects:

[0042] This invention establishes a dynamic estimation model of the junction temperature of radio frequency devices based on ambient temperature and radio frequency operating status. It combines power mutation feedforward prediction, junction temperature driven parameter compensation, and slow timescale model self-correction mechanism to make the compensation basis closer to the actual operating state of the device, significantly shorten the compensation response time, suppress transient performance degradation, and improve the communication stability, long-term reliability, and device lifespan of the vehicle 5G communication module in complex temperature and high load scenarios. Attached Figure Description

[0043] Figure 1 This is a system block diagram of an integrated edge-mounted 5G communication module for vehicles according to the present invention;

[0044] Figure 2 This is a flowchart illustrating the usage method of an integrated edge vehicle-mounted 5G communication module according to the present invention. Detailed Implementation

[0045] The following will describe in detail the implementation of this application with reference to the accompanying drawings and embodiments, so that the implementation process of how this application uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly.

[0046] like Figures 1-2 As shown in the figure, this embodiment provides an integrated edge computing vehicle 5G communication module and its usage method, including a 5G communication submodule, an edge computing submodule, a vehicle data and control interface submodule, a security and system management submodule, and a power management and physical bearer submodule. The 5G communication submodule includes a 5G baseband processing unit, a radio frequency transceiver unit, a radio frequency front-end and antenna interface unit, a network access and protocol control unit, and a radio frequency power and temperature management unit for achieving stable communication access in a vehicle environment; the radio frequency transceiver unit includes a radio frequency calibration and compensation system.

[0047] The RF calibration and compensation system combines specific methods, implemented through 1. initialization, 2. periodic main loop, event processing, 3. slow timescale self-calibration, 4. event-driven process (fast response scenario), and 5. protection and logging process. It is used to solve the problem that in the actual application of vehicle-mounted 5G communication modules, existing technologies usually deploy temperature sensors near the RF front-end devices and perform compensation based on a pre-established temperature-RF parameter mapping table. However, due to the spatial deviation between the temperature measured by the sensor and the actual junction temperature of the RF device, and the rapid rise of junction temperature and the lag in sensor response under high-power burst service scenarios, the compensation action is delayed or inaccurate. At the same time, the mapping table is also susceptible to device aging and long-term operating condition changes, which can gradually become invalid, thus causing problems such as increased instantaneous bit error rate, unstable transmission power, and decreased reliability.

[0048] Specifically:

[0049] 1. Initialization:

[0050] 11. Read or load factory calibration parameters: equivalent thermal resistance Equivalent heat capacity Prediction coefficient Sampling period Mapping table (junction temperature → compensation parameters), protection threshold , ;

[0051] 12. Calculate the initial coefficients: , ;

[0052] 13. Initialize state variables: Set Or use the previously saved ,set up ;

[0053] 14. Start the sensor sampling, RF status acquisition, and link performance acquisition modules;

[0054] 15. Write initialization information to the system log;

[0055] 2. Periodic main cycle (every Execute once; =50ms–1s), event handling:

[0056] 21. Data Acquisition: Reading temperature sensor values (If there are multiple sensors, then perform weighted fusion to obtain a single result) Read RF operating status: Current equivalent transmit power consumption Duty cycle Current frequency band / modulation information; read or estimate link performance indicators (can be collected asynchronously for self-calibration);

[0057] 22. Through Perform junction temperature estimation;

[0058] 23. Burst Power Detection and Feedforward Prediction: Calculating Power Changes: ;

[0059] like (Power jump threshold), then calculate the prediction term. ;

[0060] And the final estimated junction temperature is obtained: ;

[0061] otherwise: ;

[0062] 24. Look up / interpolate to obtain compensation parameters:

[0063] In the mapping table The key is subjected to interval switching or linear interpolation to obtain a set of compensation parameters (PA bias, LNA bias, local oscillator compensation, IQ correction coefficient, etc.).

[0064] 25. Safety inspection and compensation distribution:

[0065] Check if the compensation parameters are within the hardware safety range (such as maximum bias, current limit, etc.); if compliant, issue a compensation command to PA / LNA / baseband; record the operation log; if compensation requires reducing transmit power (derating), issue and record the command according to priority;

[0066] 26. Protection Judgment:

[0067] like It can record warning logs and send reports to higher authorities;

[0068] like Immediately implement protection measures (gradually reduce the limit → stop issuing), and report to the police and event log;

[0069] 27. Update status and exit the current cycle:

[0070] set up ;

[0071] set up ;

[0072] Waiting for the next cycle (sleep until the next) );

[0073] 3. Slow timescale self-correction:

[0074] 31. Collect historical time-series datasets (window length can be set from several minutes to several hours):

[0075] ;

[0076] 32. Perform parameter fitting (e.g., recursive least squares or RLS) on the edge calculator to adjust. , Or adjust directly , ;

[0077] 33. Calibration should only be performed when the signal-to-noise ratio is good or the workload is low to avoid miscalibration; the calibration steps should be recorded and written back to non-volatile memory after a safety check;

[0078] 34. If the performance improves after the model update, the updated parameters will be sent to the module; otherwise, the model will be rolled back and the exception will be recorded.

[0079] 4. Event-driven process (rapid response scenario):

[0080] Event: Rapid power jump (sudden upswing): Detected in the main loop. Calculate and superimpose immediately Immediately check the table and adjust the PA bias / power limit (feedforward action), and register for subsequent monitoring and evaluation of the compensation effect;

[0081] Event: Temperature sensor malfunction or missing readings:

[0082] Switch to fault-tolerant mode: Use the last valid one Alternatively, use backup values ​​from multi-sensor fusion and increase the weight of power drive items; report faults and initiate safety inspection procedures;

[0083] Event: Link performance continues to deteriorate (BER / EVM exceeds threshold):

[0084] Trigger the model self-calibration process or enter controlled derating to protect link stability;

[0085] 5. Protection and logging process:

[0086] 51. Real-time saving of time series data for key variables: , D, , Compensation parameters, link performance, and protection events;

[0087] 52. Supports remote diagnostics and FOTA: Edge units upload model update suggestions, abnormal events, and periodic statistics to the cloud / MEC;

[0088] 53. Provides a field quick calibration interface (dedicated command sequence) to facilitate quick restoration of calibration after repair or device replacement.

[0089] By establishing a dynamic estimation model for the junction temperature of RF devices based on ambient temperature and RF operating conditions, and combining power mutation feedforward prediction, junction temperature-driven parameter compensation, and a slow timescale model self-correction mechanism, the compensation basis is made closer to the actual operating conditions of the devices, significantly shortening the compensation response time, suppressing transient performance degradation, and improving the communication stability, long-term reliability, and device lifespan of the vehicle-mounted 5G communication module in complex temperature and high-load scenarios.

[0090] The foregoing description illustrates and describes several preferred embodiments of the present invention. However, as previously stated, it should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the inventive concept described herein through the foregoing teachings or techniques or knowledge in related fields. Any modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. An integrated edge-based vehicle-mounted 5G communication module, comprising a 5G communication submodule, an edge computing submodule, a vehicle data and control interface submodule, a security and system management submodule, and a power management and physical bearer submodule, wherein the 5G communication submodule includes a 5G baseband processing unit, a radio frequency transceiver unit, a radio frequency front-end and antenna interface unit, a network access and protocol control unit, and a radio frequency power and temperature management unit for achieving stable communication access in a vehicle environment; Its features are: The radio frequency transceiver unit includes a radio frequency calibration and compensation system, the system comprising: A temperature sensor is placed near the radio frequency front end to collect ambient temperature signals; The radio frequency (RF) operating status acquisition unit is used to acquire the real-time power of RF devices. and launch duty cycle Operating status parameters; Storage unit for storing the equivalent thermal resistance of the radio frequency device. and equivalent heat capacity ; The junction temperature dynamic estimation unit, based on the temperature collected by the temperature sensor, the RF operating status parameters, and the equivalent thermal resistance and equivalent thermal capacity, estimates the junction temperature of the RF device according to a discrete recursive relationship. Perform estimation to obtain the junction temperature estimate. ; The mapping and compensation unit obtains the corresponding RF compensation parameters from the pre-stored junction temperature-RF parameter mapping table based on the estimated junction temperature value and outputs them to adjust the power amplifier bias, LNA bias, local oscillator frequency compensation, or digital baseband IQ correction parameters of the RF front end.

2. The integrated edge vehicle-mounted 5G communication module according to claim 1, characterized in that: The junction temperature dynamic estimation unit adopts a discrete recursive model: ； In the formula, For the first sample The estimated junction temperature at time [time]. For the first Temperature sensor reading at the sampling time and To and , And coefficients related to the sampling period.

3. The integrated edge vehicle-mounted 5G communication module according to claim 1, characterized in that: The junction temperature dynamic estimation unit further includes a transient temperature rise prediction subunit, used to detect the RF power. During a rapid rise event, the feedforward prediction term is calculated based on the power change rate. And this prediction term is superimposed on the estimated junction temperature, that is: ； in, These are calibration coefficients used to achieve feedforward prediction and compensation for transient junction temperature rise caused by sudden launches.

4. An integrated edge-mounted 5G communication module for vehicles according to claim 1 or 3, characterized in that: It also includes a radio frequency performance feedback acquisition unit for periodically or on-demand acquisition of link performance indicators, including but not limited to: bit error rate, error vector magnitude, received signal strength indication, or uplink / downlink throughput; and a model self-correction unit for adjusting the equivalent thermal resistance based on the deviation between the link performance indicators and the expected performance. With equivalent heat capacity or , The coefficients are updated slowly using timescales or calibration corrections to adapt to device aging or long-term environmental changes.

5. The integrated edge vehicle-mounted 5G communication module according to claim 1, characterized in that: The junction temperature-RF parameter mapping table used by the mapping and compensation unit includes at least: power amplifier bias voltage / current settings, transmit power limits, LNA bias settings, local oscillator frequency deviation compensation amounts, and baseband IQ correction coefficients corresponding to different junction temperature ranges; and the mapping table supports range switching or interpolation calculation based on the estimated junction temperature value to generate specific compensation parameters.

6. An integrated edge-mounted 5G communication module for vehicles according to any one of claims 1-5, characterized in that: The system also includes multiple temperature sensors, which are respectively deployed near different key radio frequency components and near the module. The junction temperature dynamic estimation unit determines the ambient temperature based on the temperature data from the multiple temperature sensors using a weighted fusion or nearest neighbor selection method. .

7. An integrated edge-mounted 5G communication module for vehicles according to any one of claims 1-6, characterized in that: In the discrete recursive model of the junction temperature dynamic estimation unit, and The specific values ​​are determined by the following relationship: 、 ； in, The sampling period is the sampling period, and the and It is stored in the storage unit after factory calibration.

8. An integrated edge-mounted 5G communication module for vehicles according to any one of claims 1-7, characterized in that: It also includes a fault detection and protection unit, which generates an over-temperature alarm and triggers the mapping and compensation unit to perform derating control or limit transmit power protection actions when the junction temperature estimate or the temperature sensor reading exceeds a preset threshold, so as to protect the radio frequency device from damage.

9. A method of using an integrated edge vehicle-mounted 5G communication module according to any one of claims 1-8, characterized in that: Includes the following steps: Step 1: Collect the temperature near the RF front end using a temperature sensor. ; Step 2: Acquire the real-time power of the RF device and duty cycle Operating status parameters; Step 3: Based on the data described in Steps 1-2 and the known equivalent thermal resistance With equivalent heat capacity Calculate the estimated junction temperature of the RF device according to the discrete recursive relationship. : ； In the formula, , and , Sampling period Related; Step 4: Upon detection During rapid increases, the prediction term is calculated based on the rate of power change and then... Feedforward correction is obtained ; Step 5: Based on the junction temperature estimate from Step 3 or Step 4, obtain the RF compensation parameters from the junction temperature-RF parameter mapping table and perform corresponding parameter adjustments on the RF front end; Step 6: Periodically or on-demand adjust based on link performance feedback and Update slowly.

10. The method of using an integrated edge vehicle-mounted 5G communication module according to claim 1, characterized in that: In step 4, the prediction term The calculation formula is: ； In the formula, These are the coefficients determined through calibration.

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