Autonomous mode selection switching method and system for active-passive hybrid communication

Abstract

The application provides an autonomous mode selection switching method and system for active and passive mixed communication, comprising: after a low-power Internet of Things tag accesses a gateway, acquiring current radio frequency channel energy and quantizing the current radio frequency channel energy into a received signal strength indication value; taking the received signal strength indication value as a mode switching basis, initializing an energy boundary and an upper limit and a lower limit of the energy boundary; performing four-stage blind boundary search, sequentially performing slow start, fluctuation avoidance, reliability attempt and fast recovery, updating the upper limit or the lower limit of the boundary according to real-time energy change and a negative acknowledgement signal fed back by the gateway; when a difference between the upper limit and the lower limit is less than a preset termination value, determining the upper limit of the boundary as an optimal switching boundary; and the tag autonomously selects a passive backscattering communication mode or an active radio frequency communication mode according to a comparison result of the current received signal strength indication value and the optimal switching boundary.

Description

Technical Field

[0001] This invention relates to the fields of low-power Internet of Things (IoT), environmental IoT, low-power wireless communication, and active-passive hybrid radio frequency communication. Specifically, it relates to an autonomous mode selection and switching method and system for active-passive hybrid communication. Background Technology

[0002] With the large-scale deployment of IoT technology in scenarios such as smart warehousing, healthcare, asset tracking, environmental monitoring, and industrial sensing, low-power IoT tags need to operate stably for extended periods under conditions of limited battery capacity or low-energy harvesting in the environment. Traditional active communication methods typically rely on high-power radio frequency components such as local oscillators, mixers, and power amplifiers, which offer strong link robustness but also result in high instantaneous power consumption. Passive communication methods, such as backscattering, transmit information by reflecting or modulating an external carrier, achieving microwatt-level communication power consumption. However, their reliable operating range is usually limited by factors such as dual-path loss, carrier energy, obstacles, multipath fading, and interference.

[0003] To balance low power consumption and communication reliability, hybrid active-passive communication tags are gradually becoming an important direction for environmental IoT. These tags employ passive backscatter communication when channel energy is sufficient to reduce power consumption, and active radio frequency communication when channel energy is insufficient or the passive link is unreliable to ensure data delivery. However, determining the switching boundary between the two communication modes in a real-world deployment environment is a key issue for the autonomous operation of the hybrid communication system.

[0004] One straightforward approach is to set a switching threshold based on the physical distance between the tag and the gateway, using passive communication when the distance is short and active communication when the distance is long. However, in real-world scenarios, physical distance does not accurately characterize link quality: obstructions, multipath propagation, human movement, metal shelves, changes in equipment orientation, and external interference can all lead to significant differences in channel energy and link reliability at the same distance. Therefore, fixed distance thresholds or manually preset thresholds are insufficient to accommodate the mobility, heterogeneous deployment, and gateway switching of low-power IoT tags.

[0005] Among existing hybrid communication solutions, Pengyu Zhang et al.'s "Braidio: An Integrated Active-Passive Radio for Mobile Devices with Asymmetric EnergyBudgets," published at SIGCOMM in 2016, proposed a hybrid strategy for asymmetric communication systems. This strategy employs a stacked design for active BLE communication and passive RFID communication, selecting the mode based on the available battery capacity of both devices. In 2017, Matthew S. Reynolds et al.'s "A 2.4-GHz, Hybrid 10-Mb / s BPSK Backscatter and 1-Mb / s FSK Bluetooth TX With Hardware Reuse," published in IEEE Microwave and Wireless Components Letters, proposed using a Class-C power amplifier to achieve active amplification and passive keying modulation. However, due to the stacked baseband branching, manual mode switching is required. In 2022, Abu Bakar et al. published "Protean: An Energy-Efficient and Heterogeneous Platform for Adaptive and Hardware-Accelerated Battery-Free Computing" in SenSys, proposing a modular intermittent computing platform. However, it still inevitably uses commercially available 2.4GHz active RF chips and a separate passive communication sub-board, and also employs manual configuration. In summary, some solutions require manual configuration of mode-switching parameters, while others assume a stable environment or rely on offline calibration, making it difficult to quickly re-determine the optimal boundary after tags access new cells, new gateways, or changes in environmental structure. If the boundary is set too low, the tag will prematurely enter passive communication mode, causing the gateway to be unable to reliably receive data packets; if the boundary is set too high, the tag will overuse active communication, resulting in unnecessary energy consumption. Furthermore, when the tag is near the actual boundary, the received signal strength will fluctuate frequently due to noise and short-term fading. Without an anti-oscillation mechanism, the active and passive modes will switch repeatedly in a short period, further increasing system overhead and reducing communication stability.

[0006] Therefore, there is an urgent need for an autonomous mode selection switching method that does not require prior knowledge of environmental distance parameters, can autonomously search for active and passive switching boundaries using channel energy and link feedback in a low-power manner, and can suppress mode oscillations near the boundaries. Summary of the Invention

[0007] To address the shortcomings of existing technologies, the purpose of this invention is to provide an autonomous mode selection and switching method and system for hybrid active and passive communication.

[0008] The present invention provides an autonomous mode selection and switching method for active-passive hybrid communication, comprising: Step S1: After the low-power IoT tag is connected to the gateway, it completes synchronization in active communication mode, obtains the current radio frequency channel energy, and quantifies the radio frequency channel energy into a received signal strength indicator value (RSSI). Step S2: Set the energy boundary for switching between active and passive modes. Upper boundary Lower boundary Initial boundary Volatility avoidance value and termination value and initialize , , ; Step S3: Trigger the execution of the four-stage blind boundary search algorithm, and iteratively update based on the real-time RSSI and the negative acknowledgment (NAK) signal fed back by the gateway. , and ;when At that time, Determined as the optimal switching boundary The label is based on the current RSSI and The comparison results allow for the autonomous selection of the communication mode when RSSI is greater than 1. When selecting passive backscatter communication mode, if RSSI is not greater than Select active radio frequency communication mode at this time; The four-stage blind search algorithm includes: acquiring RSSI in real time and comparing it with a preset energy boundary during the slow start phase, fluctuation avoidance phase, reliability attempt phase, and fast recovery phase, respectively. Comparisons enable autonomous selection between active and passive modes.

[0009] Preferably, the signal strength indication value RSSI includes: converting the analog voltage value into a digital quantity using an analog-to-digital converter. ,in, This indicates the sample window length used for energy averaging. Indicates the first Each ADC quantization codeword.

[0010] Preferably, the termination value It is determined based on the quantization accuracy, energy sampling range, and environmental noise level of the analog-to-digital converter, and satisfies the following relationship. ;in, The standard deviation of environmental noise energy fluctuation; For the quantization accuracy of the analog-to-digital converter; ; The quantization bits of the analog-to-digital converter; and These are the upper and lower limits of the energy sampling range, respectively; The , , , , and All of these are digital quantities on the same quantization scale as RSSI.

[0011] Preferably, during the slow start phase, the tag maintains active radio frequency communication mode and reduces the current energy boundary θ at a gradually increasing descent rate; when θ decreases to no greater than the real-time RSSI, it enters the fluctuation avoidance phase.

[0012] Preferably, during the fluctuation avoidance phase, the current energy boundary is adjusted to... And the adjusted After fixing, it enters the reliability testing phase.

[0013] Preferably, the negative acknowledgment signal (NAK) fed back by the gateway is generated by the gateway when it fails to successfully receive a passive backscatter communication data packet for a preset timeout period; the gateway identifies the NAK by turning off the carrier signal, reducing the carrier energy, or sending a downlink control signal.

[0014] Preferably, during the reliability testing phase, the communication mode is switched to passive backscatter communication mode and timer T is started. RSSI and NAK are detected within the reliability detection window corresponding to timer T. If no NAK is received within the reliability detection window and RSSI remains greater than a certain value, the test is conducted. If so, determine that the current boundary can support passive communication, and update... If no NAK is received within the reliability detection window and the RSSI drops to less than 1%, then... If a channel energy fluctuation is detected, the system returns to the slow start phase; if a NAK is received, the system determines that the current boundary is below the actual reliable communication boundary and updates the boundary accordingly. And it has entered a rapid recovery phase.

[0015] Preferably, during the rapid recovery phase, the current energy boundary is... Restore to Then return to the slow start phase to search again.

[0016] An autonomous mode selection and switching system for hybrid active-passive communication provided by the present invention includes: Module M1: After the low-power IoT tag is connected to the gateway, it completes synchronization in active communication mode, obtains the current radio frequency channel energy, and quantifies the radio frequency channel energy into a received signal strength indicator value (RSSI). Module M2: Sets the energy boundary for switching between active and passive modes. Upper boundary Lower boundary Initial boundary Volatility avoidance value and termination value and initialize , , ; Module M3: Triggers the execution of the four-stage blind boundary search algorithm, iteratively updating based on real-time RSSI and the negative acknowledgment (NAK) signal from the gateway. , and ;when At that time, Determined as the optimal switching boundary The label is based on the current RSSI and The comparison results allow for the autonomous selection of the communication mode when RSSI is greater than 1. When selecting passive backscatter communication mode, if RSSI is not greater than Select active radio frequency communication mode at this time; The four-stage blind search algorithm includes: acquiring RSSI in real time and comparing it with a preset energy boundary during the slow start phase, fluctuation avoidance phase, reliability attempt phase, and fast recovery phase, respectively. Comparisons enable autonomous selection between active and passive modes.

[0017] Preferably, the signal strength indication value RSSI includes: converting the analog voltage value into a digital quantity using an analog-to-digital converter. ,in, This indicates the sample window length used for energy averaging. Indicates the first One ADC quantization codeword; The termination value It is determined based on the quantization accuracy, energy sampling range, and environmental noise level of the analog-to-digital converter, and satisfies the following relationship. ;in, The standard deviation of environmental noise energy fluctuation; For the quantization accuracy of the analog-to-digital converter; ; The quantization bits of the analog-to-digital converter; and These are the upper and lower limits of the energy sampling range, respectively; The , , , , and All are digital quantities on the same quantization scale as RSSI; During the slow start phase, the tag maintains active radio frequency communication mode and reduces the current energy boundary θ at a gradually increasing rate of decrease; when θ decreases to no greater than the real-time RSSI, it enters the fluctuation avoidance phase. During the fluctuation avoidance phase, the current energy boundary is adjusted to and the adjusted After fixation, proceed to the reliability testing phase; The negative acknowledgment signal (NAK) fed back by the gateway is generated by the gateway when it fails to successfully receive a passive backscatter communication data packet for a preset timeout period; the gateway identifies the NAK by turning off the carrier signal, reducing the carrier energy, or sending a downlink control signal; During the reliability testing phase, the communication mode is switched to passive backscatter communication mode and timer T is started. RSSI and NAK are detected within the reliability detection window corresponding to timer T. If no NAK is received within the reliability detection window and RSSI remains greater than a certain value, the test is successful. If so, determine that the current boundary can support passive communication, and update... If no NAK is received within the reliability detection window and the RSSI drops to less than 1%, then... If a channel energy fluctuation is detected, the system returns to the slow start phase; if a NAK is received, the system determines that the current boundary is below the actual reliable communication boundary and updates the boundary accordingly. And it has entered a rapid recovery phase; During the rapid recovery phase, the current energy boundary is... Restore to Then return to the slow start phase to search again.

[0018] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention transforms the basis for switching between active and passive communication modes from ambiguous physical distance to a channel energy boundary that can be measured in real time, enabling it to adapt to real-world environmental changes such as obstruction, multipath, interference, and tag movement. 2. This invention autonomously converges to the optimal handover boundary through blind boundary search without the need for manual calibration or prior environmental knowledge, and is suitable for scenarios where tags access new gateways, new cells, or where the deployment environment changes; 3. This invention balances search speed and stability through a slow start and fluctuation avoidance mechanism, which can reduce active and passive mode oscillations caused by short-term RSSI fluctuations near the boundary. 4. This invention only requires a low-power controller to perform simple state machine, comparison, timing and boundary update operations, making it suitable for resource-constrained low-power IoT tag implementations. Attached Figure Description

[0019] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a flowchart of the autonomous mode selection and switching method for the active-passive hybrid communication used in this invention; Figure 2 This is a schematic diagram of the four-stage blind boundary search algorithm used in this invention. Detailed Implementation

[0020] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0021] Example 1 The present invention provides an autonomous mode selection and switching method for active-passive hybrid communication, comprising: Step S1: After the low-power IoT tag is connected to the gateway, it completes synchronization in active communication mode, obtains the current radio frequency channel energy, and quantifies the radio frequency channel energy into a received signal strength indicator value (RSSI). Specifically, the Signal Strength Indication (RSSI) value refers to the value obtained by converting an analog voltage value into a digital quantity using an analog-to-digital converter. The mathematical formula is as follows: ,in This indicates the sample window length used for energy averaging. Indicates the first Each ADC quantization codeword.

[0022] Step S2: Set the energy boundary for switching between active and passive modes. Upper boundary Lower boundary Initial boundary Volatility avoidance value and termination value and initialize , , ; Wherein, the termination value The parameters are determined based on the quantization accuracy, energy sampling range, and ambient noise level of the analog-to-digital converter, and satisfy the following relationship. ;in, This indicates the quantization precision of the analog-to-digital converter. , The quantization bits of the analog-to-digital converter, for example: in an 8-bit ADC. , and These are the upper and lower limits of the energy sampling range, respectively. For example, in an 8-bit ADC, the supply voltage range is 0–3.3V. , ; The standard deviation of environmental noise energy fluctuation is an empirical value obtained by statistical analysis of the labels in the working environment.

[0023] The , , , , and All of these are digital quantities on the same quantization scale as RSSI.

[0024] Step S3: Trigger the execution of the four-stage blind boundary search algorithm, and iteratively update based on the real-time RSSI and the negative acknowledgment (NAK) signal fed back by the gateway. , and ;when At that time, Determined as the optimal switching boundary The label is based on the current RSSI and The comparison results allow for the autonomous selection of the communication mode when RSSI is greater than 1. When selecting passive backscatter communication mode, if RSSI is not greater than Select active radio frequency communication mode at this time; The four-stage blind search algorithm includes: acquiring RSSI in real time and comparing it with a preset energy boundary during the slow start phase, fluctuation avoidance phase, reliability attempt phase, and fast recovery phase, respectively. Comparison enables autonomous selection between active and passive modes; The slow start phase involves the tag maintaining active radio frequency communication mode and gradually decreasing the current energy boundary at an increasing descent rate. From the initial boundary The initial search phase is gradually pushed down to near the real-time received signal strength indication (RSSI) value. The purpose is to gradually accelerate the energy boundary so that it can quickly approach the actual active-passive switching boundary without any prior information about distance or environment, while avoiding overshoot caused by excessive step size. The fluctuation avoidance phase is at the current energy boundary. When it has dropped to near the real-time RSSI, Further reduce the fixed volatility aversion value. The transition phase remains unchanged; its purpose is to reserve a margin between the energy boundary and the real-time RSSI to suppress frequent oscillations of active and passive modes caused by noise, short-term fading or small changes in path loss. The reliability testing phase involves switching the tag to passive backscatter communication mode under the energy boundary fixed after fluctuation avoidance, and during the timer... Within the corresponding reliability detection window, the real-time RSSI and the negative acknowledgment (NAK) signal fed back by the gateway jointly determine whether the current boundary can support the verification phase of reliable passive communication; its purpose is to provide a basis for subsequent boundary upper bounds. and the lower world The update provides a criterion and distinguishes transient disturbances from persistent unreliability through windowed timing; The fast recovery phase refers to the process where, during the reliability attempt phase, the current energy boundary is determined to be unreliable. One-time recovery to the currently known reliable upper bound The algorithm then returns to the rollback phase of the slow start phase. The purpose of this is to avoid the algorithm making ineffective passive communication attempts near the falsified low boundary, thereby improving the convergence speed and reducing unnecessary passive communication power consumption.

[0025] The negative acknowledgment signal (NAK) fed back by the gateway is generated by the gateway when it fails to receive a passive backscatter communication data packet for a preset timeout period; the gateway identifies the NAK by turning off the carrier signal, reducing the carrier energy, or sending a downlink control signal.

[0026] During the slow start phase, the active radio frequency communication mode is maintained, and the current energy boundary θ is reduced at a gradually increasing rate. When θ decreases to no greater than the real-time RSSI, the fluctuation avoidance phase is entered.

[0027] During the fluctuation avoidance phase, the current energy boundary is adjusted to and the adjusted After fixing, the reliability testing phase begins.

[0028] During the reliability testing phase, the communication mode is switched to passive backscatter communication mode and timer T is started. RSSI and NAK are detected within the reliability detection window corresponding to timer T. If no NAK is received within the reliability detection window and RSSI remains greater than a certain value, the test is successful. If so, determine that the current boundary can support passive communication, and update... If no NAK is received within the reliability detection window and the RSSI drops to less than 1%, then... If a channel energy fluctuation is detected, the system returns to the slow start phase; if a NAK is received, the system determines that the current boundary is below the actual reliable communication boundary and updates the boundary accordingly. And it has entered a rapid recovery phase.

[0029] During the rapid recovery phase, the current energy boundary is... Restore to Then return to the slow start phase to search again.

[0030] The present invention also provides an autonomous mode selection and switching system for hybrid active and passive communication. The autonomous mode selection and switching system for hybrid active and passive communication can be implemented by executing the process steps of the autonomous mode selection and switching method for hybrid active and passive communication. That is, those skilled in the art can understand the autonomous mode selection and switching method for hybrid active and passive communication as a preferred embodiment of the autonomous mode selection and switching system for hybrid active and passive communication.

[0031] This invention can autonomously discover the energy switching boundary of active and passive communication without prior knowledge of deployment distance and environmental parameters, suppress frequent mode oscillations near the boundary, improve the communication reliability of low-power IoT devices in complex dynamic scenarios, and reduce average communication power consumption.

[0032] Example 2 Example 2 is a preferred example of Example 1. The present invention provides an autonomous mode selection and switching method for hybrid active-passive communication, applicable to low-power IoT tags that simultaneously possess active radio frequency communication capabilities and passive backscatter communication capabilities. For example... Figure 1 As shown, the gateway provides carrier, beacon, and link feedback. The tag obtains the current channel RSSI through the energy detection branch and performs boundary search and mode switching in the low-power controller.

[0033] When a tag connects to a gateway, it is preferable to first use the active communication mode to complete synchronization and association. The active communication mode offers stronger link robustness, which is beneficial for tags to receive gateway beacons and establish initial communication relationships in unknown environments. After association is complete, the tag sets a higher initial boundary. This makes it inclined to use reliable active communication in the initial stage of the search, and sets the upper bound of the boundary. Set as Lower boundary Setting it to 0 sets the current boundary θ to 0. .

[0034] In this embodiment, RSSI is the digital quantity of channel energy obtained by the tag through a low-power energy detection circuit or RF front-end. This RSSI is not limited to the output of a specific chip; it can also be obtained jointly by passive envelope detection, a low-speed analog-to-digital converter, and processor filtering. As long as it can characterize the energy level of the current gateway carrier or target RF signal at the tag, it can be used as the basis for mode selection in this invention.

[0035] During mode selection, if the RSSI is greater than the currently used handover boundary, the current environmental energy is considered sufficient to support the backscatter link, and the tag selects the passive communication mode; if the RSSI is not greater than the handover boundary, the passive link is considered to have unreliability risks, and the tag selects the active communication mode. Since the actual reliable boundary is not explicitly known after the tag connects to a new gateway or the environment changes, the tag obtains the optimal boundary through the following four-stage blind boundary search.

[0036] like Figure 2 As shown, the four-stage blind boundary search algorithm operates in the form of a state machine. The first stage is the slow start stage. The label is in active communication mode and gradually lowers the current boundary. The boundary descent rate can be increased with each search round, for example, by increasing the step size by a fixed amount each round, or by increasing it exponentially or piecewise linearly. This design allows the algorithm to quickly approximate the true boundary when it is far from it, and avoids overshoot when it is close to it.

[0037] When the current boundary It dropped to near the real-time RSSI, i.e. At this point, the label enters the second stage, the volatility avoidance stage. The label will further... Reduce volatility aversion value Specifically This step creates a margin between the boundary and the current RSSI, thereby preventing the tag from switching back and forth between active and passive modes due to measurement noise, transient fading, or small changes in link loss.

[0038] The third phase is the reliability testing phase. The labels are adjusted... The system then enters passive backscatter communication mode and starts timer T. The time window corresponding to timer T is used to verify the reliability of passive communication under the current boundary. Within this window, the tag continuously or periodically detects RSSI and listens for whether the gateway returns NAK.

[0039] If the tag does not receive NAK within timer T and RSSI is always greater than 1, then... This indicates that the passive communication corresponding to the current boundary can maintain a stable link, and the algorithm will... Updated to This is done to narrow down the constraint interval and attempt to find a lower reliable energy boundary. If the RSSI drops to less than [value missing] within timer T... If a NAK is received within timer T, it indicates that energy fluctuations are occurring in the current environment. The tag does not immediately update its upper and lower bounds but instead returns to the slow start phase to re-search based on the real-time RSSI. If NAK is received within timer T, it means the gateway has failed to reliably receive the tag's passive communication data packets, and the current boundary is below the actual reliable communication boundary. The algorithm will then... Updated to .

[0040] The fourth phase is the fast recovery phase. After the tag receives the NAK and updates its lower bound, to avoid continuing to attempt passive communication near the unreliable lower bound, the tag quickly recovers the current boundary θ to... Then, it re-enters the slow start phase. Through this method, the algorithm lowers the upper bound when a reliable attempt succeeds and raises the lower bound when passive communication fails, continuously narrowing the constraint interval. .

[0041] when When the algorithm meets the termination condition, it outputs... As the optimal switching boundary, using the upper bound as the final boundary can preserve the communication reliability margin in the convergence result and reduce passive link failures caused by excessively low boundaries. The quantization range can be determined based on the ADC quantization accuracy, environmental noise level, service reliability requirements, and controller computational overhead. For example, in an implementation of a 12-bit ADC with a quantization range of [0, 4095], It can be taken as several units of quantification.

[0042] Example 3 This embodiment illustrates the implementation of gateway feedback NAK. The gateway maintains a local receive timer for each associated tag. When the gateway fails to successfully receive a passive backscatter data packet within the tag's allocated time slot or predetermined response window, it determines that the current passive link is unreliable and generates a NAK. To enable low-power tags to identify this feedback using a simple energy detection method, the gateway can briefly shut down the carrier or change the carrier energy, causing a detectable steep drop edge in the tag's RSSI. After detecting this edge, the tag parses it as a NAK event.

[0043] In another implementation, NAK can also be carried in the gateway downlink control frame, OOK modulation signal, wake-up signal, or other low-power detectable link feedback signal. Regardless of the specific physical form used, as long as the feedback can characterize that the gateway has not reliably received tag passive communication data packets, it can be used for lower bound updates in this invention.

[0044] Example 4 This embodiment illustrates a system implementation. The system includes a gateway and a low-power IoT tag. The tag includes an energy detection module, a low-power controller, a passive communication module, and an active communication module. The energy detection module is used to output RSSI; the low-power controller is used to execute the blind boundary search algorithm and maintain... , , , and The system controls parameters such as power domain switching; the passive communication module transmits data via backscattering when channel energy is sufficient; the active communication module actively generates radio frequency carriers and transmits data when channel energy is insufficient or the passive link is unreliable.

[0045] The low-power controller can be implemented using a microcontroller, system-on-a-chip, programmable logic device, or application-specific integrated circuit. Since the core calculations of this invention include numerical comparison, addition and subtraction, maximum value constraints, timer state judgment, and state machine transitions, it can run on resource-constrained low-power controllers without relying on complex floating-point operations or high-power RF ranging.

[0046] In actual deployments, when tags move, gateways change, obstructions occur, or channel interference increases, the current... It may become invalid. If the label is in use at this time... If NAK is continuously received afterward, or if the RSSI statistical distribution changes significantly, the label can be reinitialized. , and And then perform a four-stage blind boundary search again to adapt to the new communication environment.

[0047] Those skilled in the art will understand that, in addition to implementing the system, apparatus, and their modules provided by this invention in purely computer-readable program code, the same program can be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system, apparatus, and their modules provided by this invention can be considered a hardware component, and the modules included therein for implementing various programs can also be considered structures within the hardware component; alternatively, modules for implementing various functions can be considered both software programs implementing the method and structures within the hardware component.

[0048] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for autonomous mode selection and switching in a hybrid active-passive communication system, characterized in that, include Step S1: After the low-power IoT tag is connected to the gateway, it completes synchronization in active communication mode, obtains the current radio frequency channel energy, and quantifies the radio frequency channel energy into a received signal strength indicator value (RSSI). Step S2: Set the energy boundary for switching between active and passive modes. Upper boundary Lower boundary Initial boundary Volatility avoidance value and termination value and initialize , , ; Step S3: Trigger the execution of the four-stage blind boundary search algorithm, and iteratively update based on the real-time RSSI and the negative acknowledgment (NAK) signal fed back by the gateway. , and ;when At that time, Determined as the optimal switching boundary The label is based on the current RSSI and The comparison results allow for the autonomous selection of the communication mode when RSSI is greater than 1. When selecting passive backscatter communication mode, if RSSI is not greater than Select active radio frequency communication mode at this time; The four-stage blind search algorithm includes: acquiring RSSI in real time and comparing it with a preset energy boundary during the slow start phase, fluctuation avoidance phase, reliability attempt phase, and fast recovery phase, respectively. Comparisons enable autonomous selection between active and passive modes.

2. The autonomous mode selection and switching method for active-passive hybrid communication according to claim 1, characterized in that, The Signal Strength Indication (RSSI) value includes: converting analog voltage values ​​into digital quantities using an analog-to-digital converter. ,in, This indicates the sample window length used for energy averaging. Indicates the first Each ADC quantization codeword.

3. The autonomous mode selection and switching method for active-passive hybrid communication according to claim 1, characterized in that, The termination value It is determined based on the quantization accuracy, energy sampling range, and environmental noise level of the analog-to-digital converter, and satisfies the following relationship. ;in, The standard deviation of environmental noise energy fluctuation; For the quantization accuracy of the analog-to-digital converter; ; The quantization bits of the analog-to-digital converter; and These are the upper and lower limits of the energy sampling range, respectively; The , , , , and All of these are digital quantities on the same quantization scale as RSSI.

4. The autonomous mode selection and switching method for active-passive hybrid communication according to claim 1, characterized in that, During the slow start phase, the tag maintains active radio frequency communication mode and reduces the current energy boundary θ at a gradually increasing rate of decrease; when θ decreases to no greater than the real-time RSSI, it enters the fluctuation avoidance phase.

5. The autonomous mode selection and switching method for active-passive hybrid communication according to claim 1, characterized in that, During the fluctuation avoidance phase, the current energy boundary is adjusted to And the adjusted After fixing, it enters the reliability testing phase.

6. The autonomous mode selection and switching method for active-passive hybrid communication according to claim 1, characterized in that, The negative acknowledgment signal (NAK) fed back by the gateway is generated by the gateway when it fails to successfully receive a passive backscatter communication data packet for a preset timeout period; the gateway identifies the NAK by turning off the carrier signal, reducing the carrier energy, or sending a downlink control signal.

7. The autonomous mode selection and switching method for active-passive hybrid communication according to claim 6, characterized in that, During the reliability testing phase, the communication mode is switched to passive backscatter communication mode and timer T is started. RSSI and NAK are detected within the reliability detection window corresponding to timer T. If no NAK is received within the reliability detection window and the RSSI remains greater than 1. If so, determine that the current boundary can support passive communication, and update... ; If no NAK is received within the reliability detection window and the RSSI drops to less than If a channel energy fluctuation is detected, the system returns to the slow start phase; if a NAK is received, the system determines that the current boundary is below the actual reliable communication boundary and updates the boundary accordingly. And it has entered a rapid recovery phase.

8. The autonomous mode selection and switching method for active-passive hybrid communication according to claim 1, characterized in that, During the rapid recovery phase, the current energy boundary is... Restore to Then return to the slow start phase to search again.

9. An autonomous mode selection and switching system for hybrid active-passive communication, characterized in that, include Module M1: After the low-power IoT tag is connected to the gateway, it completes synchronization in active communication mode, obtains the current radio frequency channel energy, and quantifies the radio frequency channel energy into a received signal strength indicator value (RSSI). Module M2: Sets the energy boundary for switching between active and passive modes. Upper boundary Lower boundary Initial boundary Volatility avoidance value and termination value and initialize , , ; Module M3: Triggers the execution of the four-stage blind boundary search algorithm, iteratively updating based on real-time RSSI and the negative acknowledgment (NAK) signal from the gateway. , and ;when At that time, Determined as the optimal switching boundary The label is based on the current RSSI and The comparison results allow for the autonomous selection of the communication mode when RSSI is greater than 1. When selecting passive backscatter communication mode, if RSSI is not greater than Select active radio frequency communication mode at this time; The four-stage blind search algorithm includes: acquiring RSSI in real time and comparing it with a preset energy boundary during the slow start phase, fluctuation avoidance phase, reliability attempt phase, and fast recovery phase, respectively. Comparisons enable autonomous selection between active and passive modes.

10. The autonomous mode selection and switching system for active-passive hybrid communication according to claim 9, characterized in that, The Signal Strength Indication (RSSI) value includes: converting analog voltage values ​​into digital quantities using an analog-to-digital converter. ,in, This indicates the sample window length used for energy averaging. Indicates the first One ADC quantization codeword; The termination value It is determined based on the quantization accuracy, energy sampling range, and environmental noise level of the analog-to-digital converter, and satisfies the following relationship. ;in, The standard deviation of environmental noise energy fluctuation; For the quantization accuracy of the analog-to-digital converter; ; The quantization bits of the analog-to-digital converter; and These are the upper and lower limits of the energy sampling range, respectively; The , , , , and All are digital quantities on the same quantization scale as RSSI; During the slow start phase, the tag maintains active radio frequency communication mode and reduces the current energy boundary θ at a gradually increasing rate of decrease; when θ decreases to no greater than the real-time RSSI, it enters the fluctuation avoidance phase. During the fluctuation avoidance phase, the current energy boundary is adjusted to And the adjusted After fixation, proceed to the reliability testing phase; The negative acknowledgment signal (NAK) fed back by the gateway is generated by the gateway when it fails to successfully receive a passive backscatter communication data packet for a preset timeout period; the gateway identifies the NAK by turning off the carrier signal, reducing the carrier energy, or sending a downlink control signal; During the reliability testing phase, the communication mode is switched to passive backscatter communication mode and timer T is started. RSSI and NAK are detected within the reliability detection window corresponding to timer T. If no NAK is received within the reliability detection window and RSSI remains greater than a certain value, the test is successful. If so, determine that the current boundary can support passive communication, and update... If no NAK is received within the reliability detection window and the RSSI drops to less than 1%, then... If a channel energy fluctuation is detected, the system returns to the slow start phase; if a NAK is received, the system determines that the current boundary is below the actual reliable communication boundary and updates the boundary accordingly. And it has entered a rapid recovery phase; During the rapid recovery phase, the current energy boundary is... Restore to Then return to the slow start phase to search again.

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