Wireless communication system for industrial internet of things nodes

Abstract

The application relates to the technical field of wireless communication systems of industrial internet nodes, and discloses a wireless communication system for industrial internet nodes, which comprises an interference feature extraction unit, a transient recovery parameter determination unit and a transmission lockout control unit.The interference feature extraction unit is used for locking the physical falling edge moment of a periodic high-energy interference pulse based on background noise base fluctuation features; the transient recovery parameter determination unit is used for extracting a transient recovery constant required for an automatic gain control circuit of a radio frequency front end to return from a saturated state to a linear region; and the transmission lockout control unit is used for constructing a logic transmission prohibition window, setting the termination moment of the logic transmission prohibition window as a moment that lags behind the physical falling edge moment, and setting the lag length as equal to the transient recovery constant.Through quantitative compensation of endogenous hysteresis characteristics of a radio frequency device, the application avoids a communication blind area caused by hardware gain oscillation, and realizes high determinacy and low energy consumption of data transmission in a strong interference environment.

Description

Technical Field

[0001] This invention relates to a wireless communication system for industrial IoT nodes, belonging to the technical field of wireless communication systems for industrial IoT nodes. Background Technology

[0002] Currently, in industrial automation control and field data acquisition scenarios, wireless communication systems are widely used to connect various industrial IoT nodes. In order to ensure the reliability of concurrent communication among multiple nodes under limited spectrum resources, existing wireless communication protocols usually adopt a resource scheduling mechanism based on channel state awareness. Its core operating logic is: the base station or IoT node evaluates the channel quality of the current time slot by detecting the received signal strength or signal-to-noise ratio of the physical channel; once the interference signal strength in the channel is detected to be lower than a preset threshold, it is determined that the channel is in an idle and available state, and then radio resource blocks are allocated for data transmission. This mechanism does not consider the physical recovery characteristics of the radio frequency front end, that is, the electromagnetic silence state of the physical channel is directly equivalent to the transmittable state of the communication link.

[0003] However, in industrial environments containing equipment such as high-power frequency converters, arc welding machines, or pulse power supplies, the electromagnetic environment exhibits strong pulse characteristics. These interference sources radiate high-energy electromagnetic pulses into space during operation. To address this interference, existing technologies typically improve the real-time performance of interference detection, requiring communication nodes to quickly identify the falling edge of the interference pulse so as to seize the channel immediately after the interference disappears, thereby improving spectrum utilization. However, relying solely on physical layer detection or logic synchronization control strategies has limitations when dealing with the inherent physical inertia of radio frequency devices. For example, Chinese invention patent CN115356759B discloses a functional module and positioning method that constructs a system to avoid interference by generating pulse signals from the distribution of interference signals and performing logical operations with synchronization following signals. While this scheme uses digital logic to achieve synchronous tracking and blocking of interference periods, its technical perspective is still limited to a simple binary judgment based on the presence or absence of external interference signals. It does not take into account the nonlinear recovery time required after the strong interference is removed from the RF front-end analog circuit. This strategy is based on idealized timing control logic, which causes the system to release transmission permissions prematurely before the RF devices have completely escaped the saturation oscillation state, leading to data demodulation failure. However, in actual engineering applications, even with the above-mentioned fast avoidance strategy, data transmission of industrial IoT nodes still suffers from high bit error rate and retransmission delay jitter. Analysis shows that the root cause of this problem is that the existing resource scheduling logic only focuses on changes in the external electromagnetic environment, while ignoring the physical response characteristics of the IoT node's own RF hardware under strong interference.

[0004] Therefore, how to establish a resource allocation mechanism that incorporates the analog transient recovery characteristics of the RF front end into the resource scheduling decision closed loop, and enables the data transmission timing active adapter linearity recovery window, is the technical problem to be solved by this invention. Summary of the Invention

[0005] To address the problems mentioned in the background art, the technical solution of the present invention is as follows: A wireless communication system for industrial IoT nodes, comprising:

[0006] The interference feature extraction unit is physically connected to the radio frequency receiving front end. It is used to perform received signal strength sampling in the idle time slot of the wireless channel and lock the physical falling edge time of the periodic high-energy interference pulse based on the fluctuation characteristics of the background noise floor.

[0007] The transient recovery parameter determination unit is used to store the RF front-end hardware attribute data of the IoT nodes connected to the system, and extract the RF front-end transient recovery constant required for the automatic gain control circuit of the IoT node to return from the saturation state to the linear amplification region based on the hardware attribute data.

[0008] The transmission blocking control unit is signal-connected to the interference feature extraction unit and the transient recovery parameter determination unit. It is used to construct a logical transmission-blocking window that covers high-energy interference pulses in the time domain. The transmission blocking control unit executes the following control logic: the termination time of the logical transmission-blocking window is set to lag behind the physical falling edge time, and the duration of this lag is equal to the transient recovery constant of the RF front end. It also generates a physical layer control command that allows data transmission only after the automatic gain control circuit recovers linearity, so as to ensure that data transmission avoids the nonlinear response region of the RF front end.

[0009] Preferably, the interference feature extraction unit includes a pulse edge recognition subunit, used to identify the rising and falling edge times of periodic pulses in the received signal strength, and to confirm the falling edge time as the physical falling edge time; the transmission blocking control unit calculates the duration of physical interference based on the rising edge time and the physical falling edge time, and sets the duration of the logic blocking transmission window to be a linear superposition of the duration of physical interference and the transient recovery constant of the RF front end, so as to eliminate the communication dead zone caused by the gain instability of the RF device after strong interference.

[0010] Preferably, the transmission blocking control unit calculates the total time length of the logic-prohibited transmission window based on the following core quantization rules: ,in, The total time length of the logically forbidden transmission window. The falling edge time of the interference pulse identified by the pulse edge recognition subunit. The rising edge time of the interference pulse identified by the pulse edge recognition subunit. The transient recovery constant of the RF front-end is extracted by the transient recovery parameter determination unit; the transmission latching control unit in The operation of the physical layer data transmission circuit is forcibly suppressed during the time period.

[0011] Preferably, the system further includes a clock phase calibration unit, which uses the rising edge of the periodic high-energy interference pulse locked by the interference feature extraction unit as a common passive reference clock source, calculates the drift of the local clock relative to the common passive reference clock source, and performs a phase alignment operation of the local clock according to the drift to maintain the time synchronization of the system.

[0012] Preferably, the transient recovery parameter determination unit includes a hardware characteristic mapping database, which establishes a unique mapping relationship between different RF capability level parameters and the corresponding RF front-end transient recovery constant; when an IoT node is accessed, the transient recovery parameter determination unit obtains its RF capability level parameters, and accordingly matches the settling time parameters of the node's specific low-noise amplifier and automatic gain control circuit from the hardware characteristic mapping database.

[0013] Preferably, the system further includes an interference cycle prediction unit, which is used to establish an interference cycle model based on historically sampled interference pulse data and calculate the expected arrival time of the next interference pulse; the transmission blocking control unit activates the logical blocking transmission window in advance before the actual arrival of the interference pulse based on the expected arrival time, so as to avoid data packet delivery attempts during the rising edge of the interference pulse.

[0014] Preferably, the interference feature extraction unit is configured to distinguish between random burst noise and periodic industrial interference. When the sampling results of multiple consecutive cycles show that the interference signal has a stable repetition frequency and the signal strength exceeds a preset saturation threshold, a trigger signal is output to the transient recovery parameter determination unit, thereby avoiding unnecessary recovery time compensation for non-saturated random noise.

[0015] Preferably, the transmission blocking control unit further includes a power supply circuit control subunit, which is used to cut off the power supply circuit of the IoT node radio frequency receiving front end during the logical transmission blocking window, and to close the power supply circuit only within a preset preparation time before the end of the logical transmission blocking window, so as to perform sleep energy saving by utilizing the determined interference and recovery time period.

[0016] Preferably, the system is applied in an industrial discrete manufacturing workshop environment where there are high-power pulse welding machines or variable frequency servo motors. The high-energy interference pulses are generated by the periodic operation of the high-power pulse welding machines or variable frequency servo motors, and their pulse width is in the range of 1ms to 100ms.

[0017] Preferably, the interference feature extraction unit, the transient recovery parameter determination unit, and the transmission interlocking control unit are integrated into the baseband processor of the industrial IoT node, or distributed in a cooperative communication network composed of base stations and industrial IoT nodes. The base station is responsible for broadcasting the interference period and recovery constant configuration information, and the IoT node is responsible for executing local transmission avoidance control based on the configuration information.

[0018] Compared with the prior art, the beneficial effects of the present invention are:

[0019] 1. In wireless communication of industrial IoT nodes, by introducing the analog recovery time parameter of the RF front end into the construction logic of the time-domain resource mask, the timing misalignment problem between physical channel idleness and receiver linearity recovery under strong industrial interference environment is solved. The resource mask module calculates and generates a transmission prohibition interval containing logical tails based on the physical falling edge of the environmental interference pulse and the preset hardware setup time. By mapping the transient characteristics of the analog devices in the physical layer to the digital scheduling constraints of the media access control layer, the nonlinear distortion caused by the automatic gain control circuit and low noise amplifier being in the saturation recovery period is eliminated. This ensures that the allocation of radio resource blocks is only performed after the receiver RF link has fully established a linear operating point. This design effectively avoids invalid transmissions that occur when the channel noise floor returns to normal but the device is actually in the gain oscillation stage, reducing the packet loss rate and retransmission overhead of industrial IoT nodes in pulse interference environment.

[0020] 2. This system establishes a phase synchronization mechanism between interference period and transmission scheduling, transforming the allocation mode of wireless resources from random competition based on instantaneous channel quality to active avoidance based on deterministic time-domain phase. The synchronization scheduling unit utilizes the periodic characteristics of background noise extracted by the interference feature introspection unit to limit downlink control commands and uplink data transmission within the effective scheduling window after hysteresis compensation correction. This resource mapping logic based on physical beats blocks continuous mixed automatic retransmission requests caused by periodic high-energy pulses, so that the end-to-end data transmission delay no longer follows a random probability distribution affected by interference intensity, but converges to a deterministic constant interval strongly correlated with the interference period, thereby meeting the stringent requirements of industrial closed-loop control systems for isochronism and determinism of communication links.

[0021] 3. This solution utilizes deterministic interference pulses in the environment as a common passive reference clock between the base station and IoT nodes, achieving high-precision time alignment without the need for frequent high-power synchronization signaling. The IoT nodes capture specific envelope characteristics of the interference pulses through physical layer energy detectors and calibrate the local clock drift based on the interference reference period sent by the base station and the rising edge of the locally captured pulses. This transforms the periodic electromagnetic interference, which was originally a communication obstacle, into an auxiliary beacon for system synchronization. While reducing network control signaling overhead, it also reduces the frequency and duration of wake-up required by the IoT node's RF receiving front end to maintain synchronization. Under the premise of ensuring accurate phase locking between the communication link and the interference mask, it extends the effective service life of battery-powered nodes. Attached Figure Description

[0022] Figure 1 This is a block diagram illustrating the wireless transmission blocking control principle of the interference characteristics and transient recovery mechanism of the present invention.

[0023] Figure 2 This is a diagram illustrating the transmission interlocking operation mechanism of the industrial IoT node in response to interference sources according to the present invention.

[0024] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0026] A wireless communication system for industrial IoT nodes, comprising:

[0027] The interference feature extraction unit is physically connected to the radio frequency receiving front end. It is used to perform received signal strength sampling in the idle time slot of the wireless channel and lock the physical falling edge time of the periodic high-energy interference pulse based on the fluctuation characteristics of the background noise floor.

[0028] The transient recovery parameter determination unit is used to store the RF front-end hardware attribute data of the IoT nodes connected to the system, and extract the RF front-end transient recovery constant required for the automatic gain control circuit of the IoT node to return from the saturation state to the linear amplification region based on the hardware attribute data.

[0029] The transmission blocking control unit is signal-connected to the interference feature extraction unit and the transient recovery parameter determination unit. It is used to construct a logical transmission-blocking window that covers high-energy interference pulses in the time domain. The transmission blocking control unit executes the following control logic: the termination time of the logical transmission-blocking window is set to lag behind the physical falling edge time, and the duration of this lag is equal to the transient recovery constant of the RF front end. It also generates a physical layer control command that allows data transmission only after the automatic gain control circuit recovers linearity, so as to ensure that data transmission avoids the nonlinear response region of the RF front end.

[0030] Preferably, the interference feature extraction unit includes a pulse edge recognition subunit, used to identify the rising and falling edge times of periodic pulses in the received signal strength, and to confirm the falling edge time as the physical falling edge time; the transmission blocking control unit calculates the duration of physical interference based on the rising edge time and the physical falling edge time, and sets the duration of the logic blocking transmission window to be a linear superposition of the duration of physical interference and the transient recovery constant of the RF front end, so as to eliminate the communication dead zone caused by the gain instability of the RF device after strong interference.

[0031] Preferably, the transmission blocking control unit calculates the total time length of the logic-prohibited transmission window based on the following core quantization rules: ,in, The total time length of the logically forbidden transmission window. The falling edge time of the interference pulse identified by the pulse edge recognition subunit. The rising edge time of the interference pulse identified by the pulse edge recognition subunit. The transient recovery constant of the RF front-end is extracted by the transient recovery parameter determination unit; the transmission latching control unit in The operation of the physical layer data transmission circuit is forcibly suppressed during the time period.

[0032] Preferably, the system further includes a clock phase calibration unit, which uses the rising edge of the periodic high-energy interference pulse locked by the interference feature extraction unit as a common passive reference clock source, calculates the drift of the local clock relative to the common passive reference clock source, and performs a phase alignment operation of the local clock according to the drift to maintain the time synchronization of the system.

[0033] Preferably, the transient recovery parameter determination unit includes a hardware characteristic mapping database, which establishes a unique mapping relationship between different RF capability level parameters and the corresponding RF front-end transient recovery constant; when an IoT node is accessed, the transient recovery parameter determination unit obtains its RF capability level parameters, and accordingly matches the settling time parameters of the node's specific low-noise amplifier and automatic gain control circuit from the hardware characteristic mapping database.

[0034] Preferably, the system further includes an interference cycle prediction unit, which is used to establish an interference cycle model based on historically sampled interference pulse data and calculate the expected arrival time of the next interference pulse; the transmission blocking control unit activates the logical blocking transmission window in advance before the actual arrival of the interference pulse based on the expected arrival time, so as to avoid data packet delivery attempts during the rising edge of the interference pulse.

[0035] Preferably, the interference feature extraction unit is configured to distinguish between random burst noise and periodic industrial interference. When the sampling results of multiple consecutive cycles show that the interference signal has a stable repetition frequency and the signal strength exceeds a preset saturation threshold, a trigger signal is output to the transient recovery parameter determination unit, thereby avoiding unnecessary recovery time compensation for non-saturated random noise.

[0036] Preferably, the transmission blocking control unit further includes a power supply circuit control subunit, which is used to cut off the power supply circuit of the IoT node radio frequency receiving front end during the logical transmission blocking window, and to close the power supply circuit only within a preset preparation time before the end of the logical transmission blocking window, so as to perform sleep energy saving by utilizing the determined interference and recovery time period.

[0037] Preferably, the system is applied in an industrial discrete manufacturing workshop environment where there are high-power pulse welding machines or variable frequency servo motors. The high-energy interference pulses are generated by the periodic operation of the high-power pulse welding machines or variable frequency servo motors, and their pulse width is in the range of 1ms to 100ms.

[0038] Preferably, the interference feature extraction unit, the transient recovery parameter determination unit, and the transmission interlocking control unit are integrated into the baseband processor of the industrial IoT node, or distributed in a cooperative communication network composed of base stations and industrial IoT nodes. The base station is responsible for broadcasting the interference period and recovery constant configuration information, and the IoT node is responsible for executing local transmission avoidance control based on the configuration information.

[0039] Example 1: In a discrete manufacturing workshop scenario with a high-density spot welding robot cluster, the wireless communication network faces continuous impacts from periodic high-energy electromagnetic pulses. In this scenario, industrial IoT nodes need to report critical control data within a 400ms welding cycle. On-site monitoring data shows that even in an idle state where the Received Signal Strength Indication (RSSI) indicates the channel noise floor has fallen below -90dBm, data packets sent immediately after the falling edge of the interference pulse still exhibit a bit error rate as high as 18%, leading to frequent triggering of Hybrid Automatic Repeat Requests (HARQ) and causing severe fluctuations in communication latency. To address this situation, the system activates an interference feature extraction unit. This unit is physically connected to the RF receiving front-end and performs received signal strength sampling during idle time slots. Through autocorrelation analysis of the sampling sequence, the unit identifies the physical characteristics of the periodic high-energy interference pulses and pinpoints the physical rising edge of a single welding interference pulse. With the physical falling edge time The interference feature extraction unit constructs a noise energy distribution model using received signal strength samples; the baseband processor calculates the mean of this distribution model. with standard deviation And according to the formula Determine the negative energy gradient threshold This is used to extract background noise fluctuations from the noise energy distribution model; whereby... The engineering margin coefficient, with a value range of [1.1, 1.5], represents the duration of physical interference in this specific scenario. The transient recovery parameter determination unit reads the hardware description file of the IoT node connected to the system, which records the RF front-end attributes of this specific industrial module. Based on the fact that the zero-IF receiver's output signal exhibits a limited-amplitude flat-top characteristic or a fixed-period oscillation characteristic in saturation, and its statistical variance is lower or higher than the normal thermal noise variance range, the system uses the variance regression to the thermal noise reference level as a physical characterization of the device leaving the saturation region and restoring its linear amplification capability. Since this node uses a low-cost zero-IF receiver architecture, its low-noise amplifier (LNA) and automatic gain control (AGC) circuits require an inherent analog circuit settling time to relock to the linear operating region after encountering a strong interference saturation impact higher than -20dBm. Based on this hardware attribute, the transient recovery parameter determination unit extracts the RF front-end transient recovery constant characterizing this settling time. In this embodiment, the constant is calibrated to 250. The calibration procedure includes: during the initialization phase before the IoT node accesses the network, the baseband processor controls the RF receiving front-end to capture high-energy test pulses, and after the test pulses disappear... A sliding time window is activated at regular intervals, and the real-time variance of the received signal strength within that window is calculated. When real-time variance M consecutive sampling periods satisfy At that time, record the current time as And according to the formula Determine the transient recovery constant of the RF front end , where M is the decision window length, and its value range is an integer in the range [5, 20].

[0040] Based on the above inputs, the transmission interlocking control unit constructs a logically prohibited transmission window in the time domain. Instead of employing the traditional strategy of avoiding interference solely based on physical boundaries, this unit executes hysteresis compensation logic. The transmission interlocking control unit sets the start time of the logically prohibited transmission window to […]. And force its termination time to be set to Under this mechanism, even The physical channel has been detected as idle after a certain time, but the Media Access Control (MAC) layer scheduler still determines that the current area is a transmission restricted zone and forcibly suspends the issuance of physical layer control commands. The synchronization procedure includes: the interference feature extraction unit records the physical falling edge times of P adjacent interference pulses. Calculate the time interval between adjacent pulses and extract the interference reference period. The interference feature extraction unit maintains a first-in, first-out queue with a depth of 8 to store the pulse interval data of the most recent 8 measurements. Whenever a new falling edge is captured, the system enqueues the new data and removes the oldest data, then discards the maximum and minimum values ​​from the queue. The arithmetic mean of the remaining 6 data points is calculated, which is the current interference reference period. The interference period prediction unit then uses the formula... Calculate the estimated arrival time of the next interference pulse. and arrive at system time The logic-based transmission blocking window is activated in advance within the previously preset protection time. During this logic operation, the time-domain boundary information provided by the interference feature extraction unit and the device physical constraint parameters provided by the transient recovery parameter determination unit form a core synergy. The interference feature extraction unit defines the physical recovery point of the external environment, while the transient recovery parameter determination unit defines the linearity recovery point of the internal devices. The transmission blocking control unit solves the implicit technical contradiction between physical channel idleness and receiver device blind zone by linearly superimposing the two in the time domain. It transforms the random packet loss problem caused by the nonlinear response of analog circuits into a deterministic time-domain scheduling constraint problem. This not only avoids external electromagnetic interference but also avoids the risk of demodulation failure of the RF front end during the saturation recovery period through proactive time concession. Finally, when the system time exceeds... After the threshold is reached and the automatic gain control circuit confirms that the linear amplification region has been entered, the transmission lockout control unit releases the blockade and generates a physical layer resource allocation command. Experimental results show that, upon introducing this... After the hysteresis compensation logic mask, the success rate of the first data packet transmission after the end of the interference pulse increased from 82% to over 99.9%, and the standard deviation of end-to-end communication delay converged to within 5ms.

[0041] Example 2: This example constructs a comparative test platform with rigorous logic control to verify the inclusion of... The performance of a wireless communication system with hysteresis compensation mechanism in a complex electromagnetic environment was investigated. An industry-standard RF transceiver module was selected as the device under test (DUT). This module adopts a zero-IF architecture, and the transient recovery constant of its RF front-end was studied. The test environment, pre-calibrated to 250 μs, simulated a typical discrete manufacturing environment containing periodic pulse interference sources. The interference sources were configured to generate high-energy electromagnetic pulses with a repetition period of 400 ms and a physical pulse width of 20 ms. To comprehensively evaluate the effectiveness of the technical solution, two comparative configurations were designed. The first group served as a control group, employing an existing obstacle avoidance mechanism based on pure physical channel detection. When the Received Signal Strength Indication (RSSI) was detected to be below a physical idle threshold of -90 dBm, the channel was deemed available and transmission was permitted. The second group served as the sample group of this invention, implementing the hysteresis compensation logic proposed in this invention. At the physical falling edge of the interference pulse... After that, the cumulative duration equals Logical forbidden transmission window, only when The physical layer is only allowed to send data after a certain time. To simulate real engineering disturbances, Gaussian white noise with a signal-to-noise ratio of 20dB is superimposed in the channel, and power frequency harmonic interference with a frequency of 50Hz is introduced.

[0042] The experiment continuously monitored the data transmission quality of two configurations using a sophisticated Bit Error Rate Analyzer (BERT), focusing on the transmission status of the first data packet after the end of the interference pulse. Data acquisition lasted for 1000 interference cycles. The test results of the control group showed that the average bit error rate (BER) of data packets transmitted within the first 200 μs after the physical end of the interference pulse was as high as 18.5%, with significant burst packet loss. This long-tailed bit error distribution near the falling edge confirms that the RF front-end does indeed have a physical dead zone where the signal cannot be linearly demodulated after escaping strong interference, even if the channel RSSI shows idle at this time. This time-domain misalignment between the idle RSSI and the device dead zone is the fundamental reason for the communication instability of existing technologies under strong interference environments. In contrast, the test data of the present invention's sample group shows drastically different performance characteristics due to the introduction of… With hysteresis compensation, the transmission time of all data packets is forcibly delayed until the RF front-end fully recovers its linearity. Within the same 1000 interference cycles, the success rate of the first data packet transmission after the interference ends in the sample group of this invention is consistently above 99.92%, and no burst errors caused by front-end saturation are observed. More importantly, by statistically analyzing the end-to-end communication delay distribution, the standard deviation of the delay in the sample group of this invention converges to 4.8ms, which is better than the 12.6ms of the control sample group. This data shows that although hysteresis compensation is introduced, the transmission time of all data packets is forcibly delayed until the RF front-end fully recovers its linearity. This results in an absolute transmission delay at the microsecond level, but by eliminating the millisecond-level latency jitter caused by retransmission, the overall time determinism of the system is improved by an order of magnitude.

[0043] Further gradient stress tests showed that as the interference pulse intensity gradually increased from -20dBm to 0dBm, the bit error rate of the control group deteriorated rapidly and non-linearly, approaching communication interruption at 0dBm. However, the sample group of the present invention, thanks to deterministic compensation of the device recovery characteristics, still maintained a transmission success rate of over 99.8% under strong interference of 0dBm. This result verifies that the solution of the present invention is not only effective against interference of a specific intensity, but also provides a universal protection mechanism based on the physical properties of the device that is decoupled from the interference intensity.

[0044] Example 3: In the deployment phase of industrial wireless networks involving heterogeneous hardware access, due to physical differences in the capacitor charging and discharging characteristics of the automatic gain control loop of RF transceivers in different batches of industrial IoT nodes, a fixed empirical value is used as the transient recovery constant of the RF front end. This can lead to insufficient protection or resource waste at some nodes. Therefore, this system incorporates a self-testing transient parameter calibration procedure, executed during the initialization phase before IoT nodes connect to the network. This procedure establishes unique physical constraint boundaries for each specific hardware entity. After the calibration procedure is initiated, the node's baseband processor controls the RF front-end to enter a high-impedance listening mode and temporarily shuts down all transmit links. The processor generates a simulated saturation attack test signal in the internal digital baseband, or injects a standard step signal into the antenna port via an external test instrument. The power level of this step signal is set to 0dBm, pushing the low-noise amplifier into full saturation and triggering the automatic gain control circuit to reduce the gain to the minimum limit. After maintaining this saturation state for 50ms, the test signal... The moment is instantaneously removed, and the falling edge time is less than 1μs. At this time, the baseband processor continuously reads the value of the received signal strength indicator register at a sampling rate of 1MHz, forming a response sequence R(t) that changes with time. In the early stage of signal removal, due to the charge release effect of the integrating capacitor in the analog circuit, R(t) will not fall to the thermal noise floor, but will exhibit a nonlinear exponential decay tail.

[0045] To define the critical point at which the circuit reverts from the nonlinear region to the linear region, the system does not rely on a single absolute threshold. Instead, it executes dynamic decision logic based on variance convergence. The processor constructs a sliding time window of length N sampling points and calculates the real-time variance of the R(t) sequence within this window. As the circuit gradually recovers from saturation and the residual charge is depleted, the fluctuations in R(t) will gradually converge to the random fluctuations of the ambient thermal noise. When the calculated real-time variance... For M consecutive cycles, the thermal noise variance is lower than the preset baseline variance. When the system determines that the RF front-end has recovered its linear response capability, the start time of the sliding window is recorded as follows: Based on this physical measurement process, the transient recovery constant of the RF front-end of this node is uniquely calculated as follows: Simultaneously, for real-time locking of the physical falling edge of the interference pulse, the interference feature extraction unit executes an edge detection algorithm based on energy gradient. This unit does not simply compare instantaneous power, but calculates the energy difference ΔE between two consecutive sampling windows of the received signal strength. When it satisfies... Furthermore, the system only confirms the current moment as a valid falling edge of physical interference if the average signal value remains at the noise floor level within the preset protection time. ,in, The preset negative energy gradient threshold is set to three times the standard deviation of the system's background noise to ensure that the algorithm can still distinguish the essential difference between signal deep fading and the end of interference pulses in a strong noise background. Through the combination of the above calibration procedure and decision logic, this invention transforms the abstract parameter definition into a deterministic computation process that can be executed by any standard hardware.

[0046] Example 4: To address the aging drift phenomenon that may occur during long-term operation of industrial field equipment, this system integrates an adaptive baseline calibration procedure based on historical data. During the system initialization phase, the interference feature extraction unit continuously collects at least 24 hours of idle time slot received signal strength data to construct an initial background noise statistical model and establish the thermal noise baseline variance. The initial values ​​are not fixed. As the system runs, if the inherent noise characteristics of the RF devices slowly shift due to temperature rise or aging, relying solely on factory presets or single calibration parameters may introduce decision errors. Therefore, the system periodically recalculates the real-time noise variance under the current environment, such as every 4 hours in a quiet window with no data transmission and no strong interference, and uses an exponentially weighted moving average (EWMA) algorithm to adjust the variance. Dynamic updates ensure that even in scenarios involving long-term equipment service or drastic temperature fluctuations, the system's judgment of the linear recovery critical point remains closely aligned with the current physical reality, avoiding deviations in the calculation of the no-transmission window caused by reference drift.

[0047] Furthermore, considering the potential risks of unexpected resets or power outage restarts for industrial IoT nodes, the transmission interlock control unit incorporates fail-safe recovery logic for abnormal states. When the system detects an abnormal watchdog reset or power failure event, during the power-on initialization process, the duration of the logic-locked transmission window is temporarily set to a preset maximum safe value, for example... The self-calibration of transient parameters is 1.5 times that of the previous one until a new round of transient parameter self-calibration is completed. This prevents potential communication conflicts or hardware damage caused by aggressive scheduling strategies during the non-steady-state period when parameters have not been accurately obtained. This provides additional stability assurance for the system under extreme abnormal conditions. Through the synergy of the above adaptive calibration and fault-safe mechanism, the present invention can maintain high-reliability communication performance throughout its entire life cycle.

[0048] Example 5: To address the engineering problem of unifying the energy gradient threshold when deploying the system across different scenarios, this example provides an automated threshold optimization procedure based on the statistical distribution of ambient background noise. During the silent listening phase of system power-on initialization, the interference feature extraction unit continuously collects data at a sampling rate of 100kHz. For each air interface received signal strength sample, a noise energy histogram of the local environment is constructed. The baseband processor performs Gaussian fitting on this histogram and extracts the mean of the fitted curve. with standard deviation Based on the 3σ criterion, the system sets the negative energy gradient threshold to . Where K is the engineering margin coefficient, with a default value of 1.2. This procedure transforms the abstract threshold setting into an adaptive calculation process based on actual field measurement data, eliminating the risk of decision failure due to environmental differences.

[0049] For the calibration of the critical control parameter of protection time, the system performs a false alarm rate-missed detection rate balance test. The baseband processor internally generates a series of simulated pulse falling edge signals and superimposes random noise of different intensities. The protection time window length is adjusted step by step. The system statistically analyzes the success rate of detecting true falling edges and the false alarm rate of noise fluctuations under different window lengths. The algorithm automatically seeks the method that minimizes the total error rate (false alarm rate + false negative rate). The system sets a value and solidifies it as the optimal protection time parameter under the current environment. This process ensures that the system can automatically converge to the optimal working state when facing different channel conditions, without the need for manual intervention and debugging.

[0050] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A wireless communication system for industrial IoT nodes, characterized in that, include: The interference feature extraction unit is physically connected to the radio frequency receiving front end. It is used to perform received signal strength sampling in the idle time slot of the wireless channel and lock the physical falling edge time of the periodic high-energy interference pulse based on the fluctuation characteristics of the background noise floor. The transient recovery parameter determination unit is used to store the RF front-end hardware attribute data of the IoT nodes connected to the system, and extract the RF front-end transient recovery constant required for the automatic gain control circuit of the IoT node to return from the saturation state to the linear amplification region based on the hardware attribute data. The transmission blocking control unit is signal-connected to the interference feature extraction unit and the transient recovery parameter determination unit. It is used to construct a logical transmission blocking window that covers high-energy interference pulses in the time domain. The transmission blocking control unit executes the following control logic: it sets the termination time of the logical transmission blocking window to lag behind the physical falling edge time, and the duration of this lag is equal to the transient recovery constant of the RF front end. It also generates a physical layer control command that allows data transmission only after the automatic gain control circuit restores linearity.

2. The wireless communication system for industrial IoT nodes according to claim 1, characterized in that, The interference feature extraction unit includes a pulse edge recognition subunit, which is used to identify the rising and falling edges of periodic pulses in the received signal strength and confirm the falling edge as the physical falling edge. The transmission blocking control unit calculates the duration of physical interference based on the rising edge and physical falling edge and sets the duration of the logic blocking transmission window to be a linear superposition of the duration of physical interference and the transient recovery constant of the RF front end, so as to eliminate the communication dead zone caused by the gain instability of RF devices after strong interference.

3. A wireless communication system for industrial IoT nodes according to claim 2, characterized in that, The transmission blocking control unit calculates the total time length of the logically prohibited transmission window based on the following core quantization rules: ,in, The total time length of the logically forbidden transmission window. The falling edge time of the interference pulse identified by the pulse edge recognition subunit. The rising edge time of the interference pulse identified by the pulse edge recognition subunit. The transient recovery constant of the RF front-end is extracted by the transient recovery parameter determination unit; the transmission latching control unit in The operation of the physical layer data transmission circuit is forcibly suppressed during the time period.

4. A wireless communication system for industrial IoT nodes according to claim 1, characterized in that, The system also includes a clock phase calibration unit, which uses the rising edge of the periodic high-energy interference pulse locked by the interference feature extraction unit as a common passive reference clock source, calculates the drift of the local clock relative to the common passive reference clock source, and performs phase alignment operation of the local clock based on the drift.

5. A wireless communication system for industrial IoT nodes according to claim 1, characterized in that, The transient recovery parameter determination unit includes a hardware characteristic mapping database, which establishes a unique mapping relationship between different RF capability level parameters and the corresponding RF front-end transient recovery constant. When an IoT node is connected, the transient recovery parameter determination unit obtains its RF capability level parameters and matches the settling time parameters of the node's specific low-noise amplifier and automatic gain control circuit from the hardware characteristic mapping database accordingly.

6. A wireless communication system for industrial IoT nodes according to claim 1, characterized in that, The system also includes an interference cycle prediction unit, which is used to establish an interference cycle model based on historically sampled interference pulse data and calculate the expected arrival time of the next interference pulse; the transmission blocking control unit activates the logical transmission blocking window in advance before the interference pulse actually arrives based on the expected arrival time.

7. A wireless communication system for industrial IoT nodes according to claim 1, characterized in that, The interference feature extraction unit is configured to distinguish between random burst noise and periodic industrial interference. Only when the sampling results of multiple consecutive cycles show that the interference signal has a stable repetition frequency and the signal strength exceeds the preset saturation threshold will the trigger signal be output to the transient recovery parameter determination unit.

8. A wireless communication system for industrial IoT nodes according to claim 1, characterized in that, The transmission interlock control unit also includes a power supply circuit control subunit, which is used to cut off the power supply circuit of the IoT node radio frequency receiving front end during the logical transmission inaccessibility window, and to re-close the power supply circuit only within a preset preparation time before the end of the logical transmission inaccessibility window.

9. A wireless communication system for industrial IoT nodes according to claim 1, characterized in that, The system is applied in industrial discrete manufacturing workshop environments where high-power pulse welding machines or variable frequency servo motors are present. The high-energy interference pulses are generated by the periodic operation of the high-power pulse welding machines or variable frequency servo motors, and their pulse width is in the range of 1ms to 100ms.

10. A wireless communication system for industrial IoT nodes according to claim 1, characterized in that, The interference feature extraction unit, transient recovery parameter determination unit, and transmission interlocking control unit are integrated into the baseband processor of the industrial IoT node, or distributed in a cooperative communication network composed of base stations and industrial IoT nodes. The base station is responsible for broadcasting the interference period and recovery constant configuration information, and the IoT node is responsible for executing local transmission avoidance control based on the configuration information.

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