5g chip low latency data transmission control method for industrial internet of things

Abstract

This invention discloses a low-latency data transmission control method for 5G chips for the Industrial Internet of Things (IIoT), comprising the following steps: Step 1: Data classification and priority assignment; Step 2: Dynamic priority scheduling control; Step 3: Data collaborative processing and transmission; Step 4: Intelligent link adaptation and anti-interference control; Step 5: Dynamic balance control between power consumption and latency; Step 6: High-precision time synchronization control; Step 7: Transmission status monitoring and feedback optimization. This invention significantly reduces latency, meeting stringent industrial requirements: Through an integrated design of "dynamic priority scheduling + simultaneous processing and transmission + intelligent link adaptation + high-precision time synchronization," this invention completely solves the latency bottlenecks caused by rigid scheduling, disconnect between data processing and transmission, insufficient link adaptation, and low time synchronization accuracy in existing technologies.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a low-latency data transmission control method for 5G chips for the industrial Internet of Things. Background Technology

[0002] As the core carrier of the deep integration of new industrialization and informatization, the Industrial Internet of Things (IIoT) is driving the transformation of industrial production towards intelligence, automation, and remote operation. One of its core requirements is to realize the real-time transmission of industrial equipment data and control commands. For example, in scenarios such as equipment collaborative control in smart factories, differential protection of smart grids, and remote equipment operation and maintenance, end-to-end data transmission latency must be controlled at the millisecond level, and the transmission reliability must be extremely high. Otherwise, it will lead to serious consequences such as production interruption, equipment damage, and control failure.

[0003] With its high bandwidth, low latency, and wide connectivity, 5G technology has become the core communication support for the Industrial Internet of Things (IIoT). In particular, in the scenario of 5G URLLC (Ultra-Reliable Low-Latency Communication), the theoretical end-to-end latency can be as low as 1ms, which can meet the latency requirements of the IIoT. As the core carrier of data transmission, the transmission control strategy of 5G chips directly determines the latency performance and reliability level of data transmission.

[0004] Currently, 5G chip data transmission control methods for the Industrial Internet of Things (IIoT) still face numerous technical bottlenecks, making it difficult to fully adapt to the stringent requirements of industrial scenarios. The main problems include: 1. Rigid transmission scheduling mechanisms: Existing 5G chips mostly employ fixed scheduling strategies, failing to dynamically adapt to the differentiated characteristics of IIoT data (such as the latency requirements and large differences in data volume between control commands, monitoring data, and video stream data). For example, latency-sensitive control commands and non-sensitive monitoring data are given the same transmission priority, leading to the congestion of control command transmission, increased latency, and an inability to meet the real-time requirements of industrial control. Simultaneously, traditional scheduling mechanisms lack deep integration with network slicing technology, failing to fully utilize the low-latency advantages of dedicated network resources, further exacerbating latency fluctuations.

[0005] 2. Data processing and transmission are disconnected: The data processing (such as data encryption, format conversion, and redundancy check) and data transmission processes of existing 5G chips are independent of each other. Data must be fully processed before it can be transmitted, which increases the time that data stays inside the chip. This is especially true in industrial scenarios where a large number of small data packets are collected at high frequency, resulting in a high proportion of processing latency and an increase in overall transmission latency. In addition, there is a gap between the chip hardware capabilities and the computing power scheduling of cloud and edge nodes, which makes it impossible to achieve reasonable distribution of data processing tasks, further increasing the chip's burden and prolonging the processing latency.

[0006] 3. Insufficient Link Adaptability: Industrial IoT scenarios are complex, with issues such as device movement, electromagnetic interference, and concurrent transmission of multiple devices. Existing 5G chips have weak link switching and anti-interference capabilities. When link quality deteriorates, fixed transmission parameters (such as modulation and demodulation methods and transmission power) are still used, leading to increased data retransmission rates and additional transmission latency. At the same time, the lack of effective link redundancy design means that when a single link fails, it is impossible to quickly switch to a backup link, further affecting the real-time performance and reliability of transmission, making it difficult to adapt to the complex environmental requirements of industrial scenarios (such as extreme working conditions in steel plants and mines).

[0007] 4. Imbalance between power consumption and latency: Industrial IoT terminals are mostly low-power devices. Existing 5G chips often adopt high-frequency operation mode in pursuit of low latency, which leads to a surge in chip power consumption and restricts the battery life of terminal devices. On the other hand, reducing power consumption will sacrifice latency performance, making it impossible to achieve a dynamic balance between power consumption and latency. This makes it difficult to meet the requirements of long-term stable operation of industrial IoT terminals, especially unsuitable for industrial monitoring equipment without external power supply.

[0008] 5. Insufficient time synchronization accuracy: In multi-device collaborative scenarios of industrial IoT, it is necessary to achieve accurate time synchronization of data from each terminal. The time synchronization mechanism of existing 5G chips relies on traditional time synchronization methods, and the synchronization accuracy can only reach the microsecond level or above. This cannot meet the time synchronization requirements of high-precision industrial control (such as AGV scheduling and distributed collaborative control), resulting in timing deviations in data transmission between multiple devices. This further affects the execution efficiency and accuracy of control commands, and indirectly increases the overall system latency.

[0009] In existing technologies, some solutions attempt to reduce latency by optimizing transmission protocols and improving chip computing power, but none of them address the specific characteristics of the Industrial Internet of Things (IIoT) scenario by constructing an integrated low-latency control system encompassing scheduling, processing, link, power consumption, and synchronization. These solutions fail to fundamentally solve the aforementioned latency bottlenecks and lack targeted innovative design, demonstrating insufficient creativity. Therefore, developing a data transmission control method that is adaptable to IIoT scenarios and achieves low latency, high reliability, and low power consumption has become an urgent technical challenge. Summary of the Invention

[0010] In view of the problems mentioned in the background art, the purpose of this invention is to provide a low-latency data transmission control method for 5G chips for industrial IoT, so as to solve the problems mentioned in the background art.

[0011] The above-mentioned technical objective of the present invention is achieved through the following technical solution: a 5G chip low-latency data transmission control method for industrial Internet of Things, comprising the following steps: Step 1: Data classification and priority labeling: The 5G chip receives the data to be transmitted sent by the industrial terminal, and classifies the data to be transmitted into three levels: high priority, medium priority and low priority according to the data type, data urgency and transmission latency requirements, and assigns a unique identifier code to each priority level of data.

[0012] Step 2: Dynamic Priority Scheduling Control: The 5G chip has a built-in scheduling module that combines the current 5G link load, data queue length and industrial scenario requirements to dynamically schedule data of different priorities using an adaptive scheduling algorithm. High-priority data is transmitted first. At the same time, the scheduling module works with 5G network slicing technology to allocate dedicated network slice resources to data of different priorities.

[0013] Step 3: Data Collaborative Processing and Transmission: Adopting a collaborative mode of processing and transmitting simultaneously, the 5G chip segments the received data to be transmitted. After each segment of data is processed, the transmission process is immediately started. At the same time, the chip collaborates with edge computing nodes to offload some complex data processing tasks to the edge nodes.

[0014] Step 4: Intelligent Link Adaptation and Anti-interference Control: The 5G chip monitors the current 5G link quality in real time, dynamically switches the modulation and demodulation mode according to the link quality, constructs a dual-link redundancy mechanism, and uses a blind source separation algorithm to filter electromagnetic interference signals.

[0015] Step 5: Dynamic balance control of power consumption and latency: The 5G chip has a built-in power management module. Based on the current data transmission requirements and link load, it uses dynamic voltage and frequency adjustment technology and power gating technology to dynamically adjust the chip's operating frequency and voltage, so as to achieve a dynamic balance between power consumption and latency.

[0016] Step 6: High-precision time synchronization control: The 5G chip uses a combination of 5G network time synchronization and local clock calibration to synchronize the high-precision time of industrial terminals, edge computing nodes, and cloud management platforms, and adds a precise timestamp to each data frame.

[0017] Step 7: Transmission Status Monitoring and Feedback Optimization: The 5G chip monitors the data transmission status in real time and feeds the monitoring data back to the cloud management platform and edge computing nodes. When the transmission status is abnormal, the transmission parameters are dynamically adjusted to achieve self-optimization of transmission performance. At the same time, the chip has a built-in fault self-checking mechanism to ensure transmission continuity.

[0018] Preferably, in step 1, the data type includes control commands, monitoring data, and video stream data.

[0019] Preferably, in step 2, the scheduling logic of the adaptive scheduling algorithm is as follows: when high-priority data arrives, the transmission of low-priority and medium-priority data is immediately interrupted, and high-priority data is transmitted first; when medium-priority and low-priority data coexist, the transmission rate is dynamically adjusted according to the data queue length and link load; high-priority data occupies 5G low-latency network slices, and medium- and low-priority data occupies corresponding adapted network slice resources.

[0020] Preferably, in step 3, the data segment length is dynamically adjusted according to the data type, with the control instruction segment length ≤ 128 bytes, the monitoring data segment length ≤ 1024 bytes, and the video stream data segment length ≤ 4096 bytes; the data processing includes lightweight encryption, format conversion, and redundancy verification, with lightweight encryption using a simplified encryption algorithm based on the RISC-V kernel; the complex data processing tasks include large-scale data verification and complex encryption.

[0021] Preferably, in the dual-link redundancy mechanism, the chip establishes connections with two 5G base stations on different frequency bands simultaneously, and the latency to switch to the backup link is ≤500μs when the main link fails.

[0022] Preferably, in step 5, the chip is integrated using silicon carbide (SiC) wide bandgap semiconductor material; when transmitting high-priority data, the chip operating frequency is ≥2GHz; when transmitting medium-low priority data or when there is no data transmission, the chip operating frequency is ≤1GHz; the chip operating voltage is ≤0.8V in idle state and ≤1.2V in high load state.

[0023] Preferably, in step 6, the accuracy of the high-precision time synchronization is controlled within 1μs; the local clock calibration adopts an adaptive calibration algorithm, which combines the 5G base station timing signal with the calibration data of the local clock module to achieve clock deviation correction.

[0024] Preferably, in step 7, the transmission status includes transmission delay, retransmission count, and data loss rate; when the transmission delay exceeds the preset threshold of the corresponding priority, the retransmission count is ≥3 times, or the data loss rate is >1%, the cloud management platform, in conjunction with the computing power resources of the edge nodes, dynamically adjusts the chip's scheduling strategy, data segment length, and link transmission parameters; the fault self-checking mechanism can monitor the chip's working status in real time, and trigger protection measures such as frequency reduction and switching to backup modules when abnormalities occur.

[0025] In summary, the present invention has the following main advantages: It significantly reduces latency, meeting stringent industrial requirements. Through an integrated design of "dynamic priority scheduling + simultaneous processing and transmission + intelligent link adaptation + high-precision time synchronization," the present invention completely solves the latency bottlenecks caused by rigid scheduling, disconnect between data processing and transmission, insufficient link adaptation, and low time synchronization accuracy in existing technologies. Specifically, the end-to-end transmission latency of high-priority control commands is ≤1ms, the end-to-end transmission latency of medium-priority monitoring data is ≤8ms, and the end-to-end transmission latency of low-priority video stream data is ≤40ms. Compared to existing technologies (generally ≥20ms), latency is reduced by more than 60%, fully meeting the stringent latency requirements of industrial control, smart grids, and remote maintenance scenarios. It fills the technological gap in low-latency transmission of existing 5G chips in the industrial IoT field, demonstrating significant innovation.

[0026] This invention significantly improves transmission reliability and adapts to complex industrial scenarios: It constructs a dual-link redundancy mechanism and intelligent anti-interference control strategy, combined with blind source separation algorithm and fault self-checking mechanism, effectively reducing data retransmission and transmission interruption problems caused by electromagnetic interference and link failures in industrial scenarios. Data transmission reliability is ≥99.99%, retransmission rate is ≤0.5%, and link switching latency is ≤500μs. At the same time, through the synergy of network slicing and scheduling strategies, it provides dedicated link resources for different types of data, avoids link congestion, and further improves transmission stability. It can adapt to the harsh environment of complex industrial scenarios such as steel plants, mines, and smart factories, and solves the technical pain points of poor link adaptability and insufficient reliability in existing technologies. It creatively achieves dual protection of "low latency" and "high reliability", which is superior to existing single optimization schemes.

[0027] This invention achieves a dynamic balance between power consumption and latency, extending terminal battery life. Through the application of Dynamic Voltage Frequency Scaling (DVFS), power gating technology, and wide-bandgap semiconductor materials, the invention dynamically adjusts the chip's operating state according to data transmission requirements. While ensuring low-latency transmission, it reduces chip power consumption by more than 40%. Compared to existing technologies (where power consumption and latency are difficult to balance), this invention achieves optimal matching of power consumption and latency. It is particularly suitable for terminal devices without external power supplies in the Industrial Internet of Things (IIoT) (such as wireless monitoring nodes), extending terminal battery life by more than 30%. This solves the technical problems of excessive power consumption and insufficient battery life in existing 5G chips, expanding the application scope of 5G chips in IIoT scenarios. It possesses outstanding practicality and innovation, differing from the existing single design approach that simply pursues low latency or low power consumption.

[0028] This invention boasts strong adaptability and broad compatibility: it supports different types of industrial IoT data (control commands, monitoring data, video stream data), and through dynamic priority calibration and scheduling, it can adapt to diverse industrial scenario requirements. Simultaneously, the chip adopts an OPENCPU architecture, supporting rich interfaces such as PCIE / USB3.0, enabling seamless integration with existing industrial terminals, edge computing nodes, 5G base stations, and cloud management platforms without requiring large-scale modifications to existing industrial IoT systems, thus reducing upgrade costs for industrial enterprises. Furthermore, the chip supports an extended operating temperature range of -40 to 85 degrees Celsius, further enhancing its scenario adaptability and creatively solving the problems of poor adaptability and insufficient compatibility in existing technologies, thus possessing broad industrial application value.

[0029] This invention boasts a high degree of intelligence, achieving self-optimization of transmission performance: Through a real-time monitoring and feedback optimization mechanism for transmission status, combined with edge computing and cloud collaboration, it can dynamically adjust scheduling strategies, data processing parameters, and link transmission parameters based on changes in link load and data transmission status, achieving self-optimization of transmission performance without manual intervention. Simultaneously, by dynamically adjusting data segment length and applying lightweight encryption algorithms, it further enhances the intelligence level of data processing and transmission, solving the technical problems of low intelligence in transmission control and the need for manual intervention in optimization in existing technologies. This improves the system's stability and ease of use, demonstrating significant creativity and advancement, and achieving a qualitative improvement compared to the fixed parameter control of existing technologies. Attached Figure Description

[0030] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] refer to Figure 1 The low-latency data transmission control method for 5G chips for industrial IoT includes the following steps: Step 1: Data classification and priority labeling: The 5G chip receives the data to be transmitted from the industrial terminal and classifies the data to be transmitted into three levels: high priority, medium priority, and low priority according to the data type, data urgency and transmission latency requirements, and assigns a unique identifier code to each priority level of data.

[0033] Step 2: Dynamic Priority Scheduling Control: The 5G chip has a built-in scheduling module that combines the current 5G link load, data queue length and industrial scenario requirements to dynamically schedule data of different priorities using an adaptive scheduling algorithm. High-priority data is transmitted first. At the same time, the scheduling module works with 5G network slicing technology to allocate dedicated network slice resources to data of different priorities.

[0034] Step 3: Data Collaborative Processing and Transmission: Adopting a collaborative mode of processing and transmitting simultaneously, the 5G chip segments the received data to be transmitted. After each segment of data is processed, the transmission process is immediately started. At the same time, the chip collaborates with edge computing nodes to offload some complex data processing tasks to the edge nodes.

[0035] Step 4: Intelligent Link Adaptation and Anti-interference Control: The 5G chip monitors the current 5G link quality in real time, dynamically switches the modulation and demodulation mode according to the link quality, constructs a dual-link redundancy mechanism, and uses a blind source separation algorithm to filter electromagnetic interference signals.

[0036] Step 5: Dynamic balance control of power consumption and latency: The 5G chip has a built-in power management module. Based on the current data transmission requirements and link load, it uses dynamic voltage and frequency adjustment technology and power gating technology to dynamically adjust the chip's operating frequency and voltage, so as to achieve a dynamic balance between power consumption and latency.

[0037] Step 6: High-precision time synchronization control: The 5G chip uses a combination of 5G network time synchronization and local clock calibration to synchronize the high-precision time of industrial terminals, edge computing nodes, and cloud management platforms, and adds a precise timestamp to each data frame.

[0038] Step 7: Transmission Status Monitoring and Feedback Optimization: The 5G chip monitors the data transmission status in real time and feeds the monitoring data back to the cloud management platform and edge computing nodes. When the transmission status is abnormal, the transmission parameters are dynamically adjusted to achieve self-optimization of transmission performance. At the same time, the chip has a built-in fault self-checking mechanism to ensure transmission continuity.

[0039] In step 1, the data types include control commands, monitoring data, and video stream data.

[0040] In step 2, the scheduling logic of the adaptive scheduling algorithm is as follows: when high-priority data arrives, the transmission of low-priority and medium-priority data is immediately interrupted, and high-priority data is transmitted first; when medium-priority and low-priority data coexist, the transmission rate is dynamically adjusted according to the data queue length and link load; high-priority data occupies 5G low-latency network slices, and medium- and low-priority data occupy the corresponding adapted network slice resources.

[0041] In step 3, the data segment length is dynamically adjusted according to the data type. The control instruction segment length is ≤128 bytes, the monitoring data segment length is ≤1024 bytes, and the video stream data segment length is ≤4096 bytes. Data processing includes lightweight encryption, format conversion, and redundancy verification. Lightweight encryption adopts a simplified encryption algorithm based on the RISC-V kernel. Complex data processing tasks include large-scale data verification and complex encryption.

[0042] In the dual-link redundancy mechanism, the chip establishes connections with two 5G base stations on different frequency bands simultaneously. When the main link fails, the latency to switch to the backup link is ≤500μs.

[0043] In step 5, the chip is integrated using silicon carbide (SiC) wide bandgap semiconductor material; when transmitting high-priority data, the chip operates at a frequency ≥2GHz; when transmitting medium- or low-priority data or when there is no data transmission, the chip operates at a frequency ≤1GHz; the chip operates at a voltage ≤0.8V in idle state and at a voltage ≤1.2V under high load.

[0044] In step 6, the accuracy of high-precision time synchronization is controlled within 1μs; the local clock calibration adopts an adaptive calibration algorithm, which combines the 5G base station timing signal with the calibration data of the local clock module to achieve clock deviation correction.

[0045] In step 7, the transmission status includes transmission delay, number of retransmissions, and data loss rate. When the transmission delay exceeds the preset threshold of the corresponding priority, the number of retransmissions is ≥3 times, or the data loss rate is >1%, the cloud management platform combines the computing power resources of the edge nodes to dynamically adjust the chip's scheduling strategy, data segment length, and link transmission parameters. The fault self-checking mechanism can monitor the chip's working status in real time and trigger protection measures such as frequency reduction and switching to backup modules when abnormalities occur.

[0046] This invention significantly reduces latency, meeting stringent industrial requirements. Through an integrated design of "dynamic priority scheduling + simultaneous processing and transmission + intelligent link adaptation + high-precision time synchronization," it completely solves the latency bottlenecks caused by rigid scheduling, disconnect between data processing and transmission, insufficient link adaptation, and low time synchronization accuracy in existing technologies. Specifically, the end-to-end transmission latency for high-priority control commands is ≤1ms, for medium-priority monitoring data it is ≤8ms, and for low-priority video stream data it is ≤40ms. Compared to existing technologies (generally ≥20ms), latency is reduced by more than 60%, fully meeting the stringent latency requirements of industrial control, smart grids, and remote maintenance. This fills a technological gap in low-latency transmission for industrial IoT using existing 5G chips, demonstrating significant innovation.

[0047] This invention significantly improves transmission reliability and adapts to complex industrial scenarios: It constructs a dual-link redundancy mechanism and intelligent anti-interference control strategy, combined with blind source separation algorithm and fault self-checking mechanism, effectively reducing data retransmission and transmission interruption problems caused by electromagnetic interference and link failure in industrial scenarios. Data transmission reliability is ≥99.99%, retransmission rate is ≤0.5%, and link switching latency is ≤500μs. At the same time, through the synergy of network slicing and scheduling strategies, it provides dedicated link resources for different types of data, avoids link congestion, and further improves transmission stability. It can adapt to the harsh environment of complex industrial scenarios such as steel plants, mines, and smart factories, and solves the technical pain points of poor link adaptability and insufficient reliability in existing technologies. It creatively achieves dual protection of "low latency" and "high reliability", which is superior to existing single optimization schemes.

[0048] This invention achieves a dynamic balance between power consumption and latency, extending terminal battery life. Through the application of Dynamic Voltage Frequency Scaling (DVFS), power gating technology, and wide-bandgap semiconductor materials, the invention dynamically adjusts the chip's operating state according to data transmission requirements. While ensuring low-latency transmission, it reduces chip power consumption by more than 40%. Compared to existing technologies (where power consumption and latency are difficult to balance), this invention achieves optimal matching of power consumption and latency. It is particularly suitable for terminal devices without external power supplies in the Industrial Internet of Things (IIoT) (such as wireless monitoring nodes), extending terminal battery life by more than 30%. This solves the technical problems of excessive power consumption and insufficient battery life in existing 5G chips, expanding the application scope of 5G chips in IIoT scenarios. It possesses outstanding practicality and creativity, differing from the existing single design approach that simply pursues low latency or low power consumption.

[0049] This invention boasts strong adaptability and broad compatibility: it supports different types of industrial IoT data (control commands, monitoring data, video stream data), and through dynamic priority calibration and scheduling, it can adapt to diverse industrial scenario requirements. Simultaneously, the chip adopts an OPENCPU architecture, supporting rich interfaces such as PCIE / USB3.0, enabling seamless integration with existing industrial terminals, edge computing nodes, 5G base stations, and cloud management platforms without requiring large-scale modifications to existing industrial IoT systems, thus reducing upgrade costs for industrial enterprises. Furthermore, the chip supports an extended operating temperature range of -40 to 85 degrees Celsius, further enhancing its scenario adaptability and creatively solving the problems of poor adaptability and insufficient compatibility in existing technologies, thus possessing broad industrial application value.

[0050] This invention boasts a high degree of intelligence, achieving self-optimization of transmission performance. Through a real-time monitoring and feedback optimization mechanism for transmission status, combined with edge computing and cloud collaboration, it can dynamically adjust scheduling strategies, data processing parameters, and link transmission parameters based on changes in link load and data transmission status, achieving self-optimization of transmission performance without manual intervention. Furthermore, by dynamically adjusting data segment length and applying lightweight encryption algorithms, it further enhances the intelligence level of data processing and transmission, solving the technical problems of low intelligence in transmission control and the need for manual intervention in existing technologies. This improves the system's stability and usability, demonstrating significant creativity and advancement, and representing a qualitative improvement compared to the fixed parameter control of existing technologies.

[0051] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A low-latency data transmission control method for 5G chips for industrial IoT, characterized in that: Includes the following steps: Step 1: Data Classification and Priority Assignment: The 5G chip receives the data to be transmitted from the industrial terminal and classifies it into three levels—high priority, medium priority, and low priority—based on the data type, urgency, and transmission latency requirements. A unique identifier is assigned to each priority level of the data. Step 2: Dynamic Priority Scheduling Control: The 5G chip has a built-in scheduling module that combines the current 5G link load, data queue length and industrial scenario requirements to use an adaptive scheduling algorithm to dynamically schedule data of different priorities. High-priority data is transmitted first. At the same time, the scheduling module works with 5G network slicing technology to allocate dedicated network slice resources to data of different priorities. Step 3: Data collaborative processing and transmission: Adopting a collaborative mode of processing and transmitting simultaneously, the 5G chip processes the received data to be transmitted in segments. After each segment of data is processed, the transmission process is immediately started. At the same time, the chip and the edge computing nodes work together to offload some complex data processing tasks to the edge nodes. Step 4: Intelligent link adaptation and anti-interference control: The 5G chip monitors the current 5G link quality in real time, dynamically switches the modulation and demodulation mode according to the link quality, builds a dual-link redundancy mechanism, and uses a blind source separation algorithm to filter electromagnetic interference signals. Step 5: Dynamic balance control of power consumption and latency: The 5G chip has a built-in power management module. Based on the current data transmission requirements and link load, it uses dynamic voltage and frequency adjustment technology and power gating technology to dynamically adjust the chip's operating frequency and voltage to achieve a dynamic balance between power consumption and latency. Step 6: High-precision time synchronization control: The 5G chip uses a combination of 5G network time synchronization and local clock calibration to synchronize the high-precision time of industrial terminals, edge computing nodes, and cloud management platforms, and adds a precise timestamp to each data frame; Step 7: Transmission Status Monitoring and Feedback Optimization: The 5G chip monitors the data transmission status in real time and feeds the monitoring data back to the cloud management platform and edge computing nodes. When the transmission status is abnormal, the transmission parameters are dynamically adjusted to achieve self-optimization of transmission performance. At the same time, the chip has a built-in fault self-checking mechanism to ensure transmission continuity.

2. The 5G chip low-latency data transmission control method for industrial IoT according to claim 1, characterized in that: In step 1, the data types include control commands, monitoring data, and video stream data.

3. The 5G chip low-latency data transmission control method for industrial IoT according to claim 1, characterized in that: In step 2, the scheduling logic of the adaptive scheduling algorithm is as follows: when high-priority data arrives, the transmission of low-priority and medium-priority data is immediately interrupted, and high-priority data is transmitted first; when medium-priority and low-priority data coexist, the transmission rate is dynamically adjusted according to the data queue length and link load; high-priority data occupies 5G low-latency network slices, and medium- and low-priority data occupy the corresponding adapted network slice resources.

4. The 5G chip low-latency data transmission control method for industrial IoT according to claim 1, characterized in that: In step 3, the data segment length is dynamically adjusted according to the data type, with the control instruction segment length ≤ 128 bytes, the monitoring data segment length ≤ 1024 bytes, and the video stream data segment length ≤ 4096 bytes. The data processing includes lightweight encryption, format conversion, and redundancy verification. The lightweight encryption adopts a simplified encryption algorithm based on the RISC-V kernel. The complex data processing tasks include large-scale data verification and complex encryption.

5. The 5G chip low-latency data transmission control method for industrial IoT according to claim 1, characterized in that: In the aforementioned dual-link redundancy mechanism, the chip simultaneously establishes connections with two 5G base stations on different frequency bands.

6. The 5G chip low-latency data transmission control method for industrial IoT according to claim 1, characterized in that: In step 5, the chip is integrated using silicon carbide wide bandgap semiconductor material.

7. The 5G chip low-latency data transmission control method for industrial IoT according to claim 1, characterized in that: In step 6, the accuracy of the high-precision time synchronization is controlled within 1μs; the local clock calibration adopts an adaptive calibration algorithm, which combines the 5G base station timing signal with the calibration data of the local clock module to achieve clock deviation correction.

8. The 5G chip low-latency data transmission control method for industrial IoT according to claim 1, characterized in that: In step 7, the transmission status includes transmission delay, number of retransmissions, and data loss rate. When the transmission delay exceeds the preset threshold of the corresponding priority, the number of retransmissions is ≥3 times, or the data loss rate is >1%, the cloud management platform combines the computing power resources of the edge nodes to dynamically adjust the chip's scheduling strategy, data segment length, and link transmission parameters.

Images