Low-power-consumption communication method and device under communication private network

Abstract

The invention discloses a low-power-consumption communication method and device under a communication private network, and relates to the technical field related to communication, and the method comprises the steps: collecting the multi-dimensional state information of communication equipment, which at least comprises a historical service flow mode, the residual electric quantity of the equipment and the current channel quality; analyzing a power consumption strategy, determining an equipment power consumption strategy, and realizing a management strategy of low power consumption of own equipment; and sending the device power consumption strategy of each communication device to the master control node, performing arbitration based on the global network state, generating an arbitrated strategy instruction, and sending the arbitrated strategy instruction to the corresponding communication device for execution, thereby realizing global low-power-consumption communication management and control. The technical problems of local energy conservation and global network performance conflict and poor overall energy efficiency caused by lack of global collaborative dynamic power consumption management in a multi-device communication private network in the prior art are solved, the network service quality is guaranteed, network-level energy consumption dynamic optimization balance is realized, and the service life of the network is prolonged. And the overall energy efficiency and sustainable operation capability of communication are improved.

Description

Technical Field

[0001] This invention relates to the field of communication-related technologies, specifically to low-power communication methods and devices under private communication networks. Background Technology

[0002] Private communication networks typically require high reliability, strong real-time performance, and secure control. Their network equipment is often deployed in power-constrained or energy-sensitive environments, such as monitoring sites in remote areas, mobile vehicle terminals, and long-term unattended sensor nodes. Their continuous and stable operation depends not only on network performance but also severely constrained by the equipment's own energy consumption. Current low-power designs in private communication networks face the following challenges: service traffic often exhibits significant time-varying and bursty characteristics, making traditional static power management strategies ill-suited to dynamic load changes, easily leading to energy waste or performance degradation; the remaining power status of the equipment directly affects its sustainable operating time, especially in scenarios with limited energy harvesting, making it difficult to dynamically adjust the operating mode based on power levels; furthermore, wireless channel quality is constantly changing due to environmental interference and node movement, and fixed transmit power or communication cycle settings may cause unnecessary energy consumption increases during periods of high interference or miss energy-saving opportunities under high-quality channel conditions. Most existing low-power communication systems employ sleep-wake mechanisms, dynamic voltage and frequency regulation, or adaptive modulation and coding. In a communication network where multiple devices work together, local optimization often fails to achieve optimal global energy efficiency. For example, excessive sleep by a single node may lead to routing interruptions or service aggregation congestion, which in turn increases the forwarding burden on other nodes and overall energy consumption.

[0003] Therefore, in the current related technologies, there is a lack of global collaborative dynamic power consumption management in multi-device communication private networks, which leads to conflicts between local energy saving and global network performance, and poor overall energy efficiency. Summary of the Invention

[0004] This application provides a low-power communication method and apparatus for private communication networks, which solves the technical problem in the prior art of lacking global collaborative dynamic power consumption management in multi-device private communication networks, resulting in conflicts between local energy saving and global network performance, and poor overall energy efficiency. It achieves the technical effect of ensuring network service quality while realizing dynamic optimization and balance of network-level energy consumption, and improving the overall energy efficiency and sustainable operation capability of communication.

[0005] This application provides a low-power communication method under a private communication network. The method includes: collecting multi-dimensional status information of communication devices, the multi-dimensional status information including at least historical service traffic patterns, remaining power of the devices, and current channel quality; parsing power consumption strategies based on the multi-dimensional status information to determine device power consumption strategies, the device power consumption strategies being management strategies to achieve low power consumption of the devices themselves; sending the device power consumption strategies of each communication device to a master control node; arbitrating the received device power consumption strategies based on the global network status to generate arbitrated strategy instructions; sending the arbitrated strategy instructions to the corresponding communication devices; and executing the arbitrated strategy instructions to achieve global low-power communication control.

[0006] In a possible implementation, the low-power communication method under the private communication network further performs the following processing: predicting the probability distribution of the service activity of the communication device in a future period based on historical service traffic patterns and current channel quality, and generating a service activity probability curve; matching the service activity probability curve with multiple preset benchmark power consumption patterns, wherein the benchmark power consumption patterns define benchmark configurations of sleep level, wake-up period and transmit power under different service scenarios; optimizing the parameters of the matched benchmark configurations based on the remaining power of the device with the goal of minimizing local power consumption, and generating the device power consumption strategy including specific sleep duration and transmit power level.

[0007] In a possible implementation, the low-power communication method under the private communication network further performs the following processing: extracting historical service traffic patterns, describing the number of data packets arriving or the interval of communication events recorded in time series, and extracting the temporal characteristics of historical service traffic patterns, including periodic characteristics, statistical characteristics, and recent change trends; obtaining current channel quality indicators, including signal-to-noise ratio and signal received strength, quantifying the current channel quality indicators into weighting factors that affect transmission reliability, and characterizing the signal state coefficients that represent the reliability of the current transmission link; inputting the extracted temporal characteristics, the current time context information, and the weighting factors into the prediction model, and outputting the probability values ​​of service communication occurring within the next T time units; constructing a discrete-time probability sequence from the probability values ​​of service communication occurring within the next T time units; and smoothing the discrete-time probability sequence to construct a continuous or segmented continuous service activity probability curve.

[0008] In a possible implementation, the low-power communication method under the private communication network further performs the following processing: the prediction model consists of a first prediction sub-model and a second prediction sub-model in parallel; wherein, the first prediction sub-model is an autoregressive model based on time series analysis, used to capture the periodic and trend components of service traffic; the second prediction sub-model is a classification model based on a lightweight gradient boosting machine, used to learn the complex nonlinear patterns of service event occurrence; this layer performs weighted fusion of the output probabilities of the two sub-models to generate an initial future service activity probability sequence.

[0009] In a possible implementation, the low-power communication method under the private communication network further performs the following processing: identifying channel and resource contention relationships based on the device power consumption strategy; ranking communication devices and their power consumption strategies that have competition relationships according to service priority rules; adjusting the power consumption strategies of conflicting devices according to the ranking results and the global network status, wherein the adjustment includes allocating requested resources to communication devices corresponding to high-priority services and modifying the power consumption strategies of low-priority devices, including delaying service execution time, allocating alternative channels, or instructing them to enter a lower-power sleep mode; and generating and issuing arbitrated policy instructions based on the adjustment results.

[0010] In a possible implementation, the low-power communication method under the dedicated communication network further performs the following processing: when the first communication device establishes a main communication link with the master control node due to high-priority services during arbitration, the master control node identifies the estimated link margin of the main communication link; based on the estimated link margin, it schedules one or more second communication devices located in the vicinity of the first communication device and waiting to transmit non-urgent batch data; based on the first communication device and the second communication device, it generates a cooperative piggybacking instruction and sends it to the first communication device and the second communication device to load the communication tasks of the second communication device into the main communication link of the first communication device; wherein, when executing the cooperative piggybacking instruction, the strategy instruction of the first communication device is configured to reserve an auxiliary data field for the non-urgent batch data in the main communication frame transmitting its high-priority service data; the strategy instruction of the second communication device is configured to encapsulate the non-urgent batch data into the format defined by the auxiliary data field, and when the first communication device establishes the main communication link, it sends the encapsulated data to the first communication device or directly and synchronously to the master control node with an additional power lower than the power required for independent transmission to complete the piggybacking transmission.

[0011] In a possible implementation, the low-power communication method under the private communication network also performs the following processing: if the policy instruction indicates entering or maintaining a sleep mode, the communication device shuts down the main communication module and starts a low-power keep-alive heartbeat mechanism with an extended cycle; if the policy instruction indicates entering or maintaining a working mode, the communication device performs communication configuration according to the connection method, transmission power level and heartbeat cycle parameters specified in the instruction.

[0012] In a possible implementation, the low-power communication method under the private communication network also performs the following processing: the trigger condition for the low-power keep-alive heartbeat mechanism with extended startup cycle is that the communication device is detected by the master control node to be in an idle state for a duration exceeding a first preset threshold.

[0013] In a possible implementation, the low-power communication method under the private communication network further performs the following processing: identifying communication devices that are about to enter or are currently in an idle listening state, distributing cooperative sensing instructions to control the communication devices to enter an idle state and perform cooperative sensing tasks; based on the communication devices corresponding to the cooperative sensing instructions, performing local signal processing on the received radio frequency signals to detect whether target signal features exist; the communication devices encapsulate the detection results into simplified sensing data, and report it along with the main service data when they next perform service communication or heartbeat reporting to the master control node.

[0014] This application also provides a low-power communication device under a private communication network. The device includes: a device status information acquisition module, used to acquire multi-dimensional status information of communication devices, the multi-dimensional status information including at least historical service traffic patterns, remaining device power, and current channel quality; a power consumption policy parsing module, used to parse power consumption policies based on the multi-dimensional status information to determine device power consumption policies, the device power consumption policies being management policies to achieve low power consumption of the devices themselves; and a policy instruction generation module, used to send the device power consumption policies of each communication device to the master control node, arbitrate the received device power consumption policies based on the global network status, generate arbitrated policy instructions, send them to the corresponding communication devices, and execute the arbitrated policy instructions to achieve global low-power communication control.

[0015] This application proposes a low-power communication method and apparatus for private communication networks. The method collects multi-dimensional status information of communication devices, including at least historical service traffic patterns, remaining device power, and current channel quality. It then performs power consumption strategy analysis to determine the device's power consumption strategy and implements a low-power management strategy for each device. The device power consumption strategies of each communication device are sent to the master control node, where arbitration is performed based on the global network status. Arbitrated strategy instructions are generated and sent to the corresponding communication devices for execution, thereby achieving global low-power communication control. This solves the technical problem in existing multi-device private communication networks where the lack of globally coordinated dynamic power consumption management leads to conflicts between local energy saving and global network performance, resulting in suboptimal overall energy efficiency. The method achieves the technical effect of ensuring network service quality while realizing dynamic optimization and balance of network-level energy consumption, improving overall communication energy efficiency and sustainable operation capabilities. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments of this disclosure will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the apparatus according to the embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0017] Figure 1 This is a schematic flowchart of a low-power communication method under a private communication network provided in an embodiment of this application.

[0018] Figure 2 This is a schematic diagram of the structure of a low-power communication device under a private communication network provided in an embodiment of this application.

[0019] Explanation of reference numerals in the attached diagram: Device status information acquisition module 10, power consumption strategy parsing module 20, strategy instruction generation module 30. Detailed Implementation

[0020] To further illustrate the technical means and effects adopted by the present invention in order to achieve the intended purpose, the following detailed description is provided in conjunction with the accompanying drawings and preferred embodiments, based on the specific implementation methods, structures, features and effects of the present invention.

[0021] This application provides a low-power communication method under a private communication network, such as... Figure 1 As shown, the method includes: Step S100: Collect multi-dimensional status information of the communication device. The multi-dimensional status information includes at least historical service traffic patterns, remaining battery power of the device, and current channel quality.

[0022] Preferably, the monitoring software on the communication equipment collects multi-dimensional status information of the communication equipment from the equipment hardware registers, operating system kernel, communication protocol stack, and log system. This information includes at least historical service traffic patterns, remaining battery power, and current channel quality. Specifically, historical service traffic patterns refer to quantifiable records of the quantity, type, and time-series distribution of various communication services within a specified time window, reflecting the equipment's service patterns and load characteristics. This may include time-series data such as the number of uplink / downlink data packets, the number of bytes transmitted, and the number of service sessions, as well as service characteristic parameters such as traffic cycle characteristics, statistical characteristics, and the proportion of traffic for different service types. Remaining battery power is a physical quantity and derived parameter reflecting the current available energy of the communication equipment. It is a key constraint determining the urgency of energy conservation. This may include power state parameters such as the current absolute capacity of the battery and the percentage of remaining power, energy prediction parameters, and power consumption-related parameters. Current channel quality refers to the performance indicators of the wireless transmission link of the communication equipment in a specified frequency band and time slot, which is a direct factor affecting communication energy efficiency. This may include signal-to-noise ratio, bit error rate, channel state information, received signal strength, data packet reception success rate, round-trip time, adjacent channel interference power, and spectrum occupancy measurement.

[0023] Step S200: Based on the multi-dimensional state information, perform power consumption strategy analysis to determine the device power consumption strategy, which is a management strategy to achieve low power consumption of the device itself.

[0024] Step S200 further includes step S210, predicting the probability distribution of the service activity of the communication device in a future period based on historical service traffic patterns and current channel quality, and generating a service activity probability curve; step S220, matching the service activity probability curve with multiple preset benchmark power consumption patterns, wherein the benchmark power consumption patterns define the benchmark configurations of sleep level, wake-up period and transmit power under different service scenarios; step S230, with the goal of minimizing local power consumption, optimizing the parameters of the matched benchmark configurations in combination with the remaining power of the device, and generating the device power consumption strategy that includes specific sleep duration and transmit power level.

[0025] Preferably, power consumption strategy analysis is performed based on multi-dimensional state information. This involves using collected historical service traffic patterns, remaining device power, and current channel quality to automatically calculate specific operating parameters that minimize device power consumption in the current and future periods through optimization rules. Specifically, historical service traffic patterns of the communication device are obtained to provide long-term communication habits and statistical patterns. These are combined with the current channel quality to predict the probability distribution of the communication device's service activity in the future period. This is the predicted probability of communication events requiring the device's participation occurring within the corresponding time unit. These service activity probabilities are then smoothly connected to form a service activity probability curve that varies with time.

[0026] Preferably, the baseline power consumption mode refers to a policy template pre-configured in the device firmware. Each policy template is designed for a typical service scenario. Each policy template contains three core parameters: sleep level (e.g., deep sleep, shallow sleep, idle listening), wake-up period (e.g., the time interval between when the device actively wakes up from sleep to check the channel or report a heartbeat, such as 1 second, 10 seconds, or 1 minute), and transmit power level (e.g., the RF power level used when data needs to be transmitted, such as maximum power, medium power, or minimum power). The similarity between the service activity probability curve and the ideal probability curves of multiple preset baseline power consumption modes is calculated, or the proportion of time when the probability exceeds a certain threshold is judged to meet the characteristics of a certain mode. This is to match the baseline mode that best fits the current prediction as the starting point for parameter optimization, ensuring decision-making efficiency and reliability. Then, the remaining battery power of the device is introduced as a hard constraint. With the goal of minimizing local power consumption, the parameters of the matched baseline configuration are fine-tuned and optimized to generate a device power consumption strategy that includes specific sleep duration and transmit power level. For example, when the "intermittent service mode" is matched, its wake-up cycle is 10 seconds. If the battery is sufficient, it may be optimized to 8 seconds. If the battery is critically low, it will be optimized to 15 seconds. Similarly, the transmit power level is also jointly adjusted according to the current channel quality and battery power. When the channel is good and the battery power is low, the power is reduced. When the channel is poor but the battery power is high, a higher power is maintained to ensure the success rate.

[0027] Furthermore, step S210 also includes step S211, extracting historical service traffic patterns, describing the number of data packets arriving or the interval of communication events recorded in time series, and extracting the temporal characteristics of historical service traffic patterns, including periodic characteristics, statistical characteristics, and recent change trends; step S212, obtaining current channel quality indicators, including signal-to-noise ratio and signal received strength, quantifying the current channel quality indicators into weighting factors affecting transmission reliability, and a signal state coefficient characterizing the reliability of the current transmission link; step S213, inputting the extracted temporal characteristics, the current time context information, and the weighting factors into the prediction model, and outputting the probability value of service communication occurring within the next T time units; step S214, constructing a discrete-time probability sequence from the probability values ​​of service communication occurring within the next T time units; and step S215, smoothing the discrete-time probability sequence to construct a continuous or segmented continuous service activity probability curve.

[0028] Preferably, historical service traffic patterns are extracted, describing the number of data packets arriving or the intervals of communication events recorded in a time series. The data packet arrival sequence records the number of IP / UDP / TCP data packets arriving at or being sent by the device within equal-length time slots. The communication event interval sequence records the timestamps of each communication event, such as a complete TCP connection, a SIP session, or a sensor data report. Then, the temporal characteristics of the historical service traffic patterns are extracted, including periodic characteristics, statistical characteristics, and recent trends. The periodic characteristics involve performing spectral analysis on the aggregated sequence of data packet arrival sequences or event intervals, such as Fast Fourier Transform (FFT) or autocorrelation analysis, to identify the main period lengths and their corresponding power spectral density amplitudes. The statistical characteristics are statistics calculated within a sliding time window, such as mean, variance, standard deviation, and extreme values. The recent trends involve performing linear or polynomial regression on the recent data packet arrival sequences or calculating their relative rate of change with the mean of earlier periods, outputting the trend slope.

[0029] Preferably, the current channel quality indicators, including signal-to-noise ratio (SNR) and signal received strength, are read from the register of the device's wireless network card / baseband chip. The SNR is the ratio of signal power to noise power; the higher the value, the cleaner the signal. The signal received strength is the power of the received radio frequency signal; the higher the value, the stronger the signal. Then, through an empirical mapping function, the current channel quality indicators are quantified into weighting factors that affect transmission reliability, i.e., correction coefficients that affect the probability of successful service communication, and signal state coefficients that characterize the reliability of the current transmission link. Next, the extracted temporal features, the current time context information, and weighting factors are input into the prediction model. The output is the predicted probability that at least one business communication event will occur within the t-th time unit in the future, given the current and historical information X. This determines the probability values ​​of business communication occurring within the next T time units and arranges them in chronological order to form a discrete-time probability sequence. Finally, the discrete-time probability sequence is smoothed, possibly by moving average, low-pass filtering, or spline interpolation, to eliminate random noise or abrupt changes that may be generated by the model prediction, forming a smoother business activity probability curve that better reflects the continuous changes in business in the physical world. For any future time, a continuous quantitative estimate of the business activity level near that time is given.

[0030] Furthermore, step S213 also includes that the prediction model is composed of a first prediction sub-model and a second prediction sub-model in parallel; wherein, the first prediction sub-model is an autoregressive model based on time series analysis, used to capture the periodic and trend components of business traffic; the second prediction sub-model is a classification model based on a lightweight gradient boosting machine, used to learn the complex nonlinear patterns of business events; this layer performs weighted fusion of the output probabilities of the two sub-models to generate an initial future business activity probability sequence.

[0031] Preferably, the prediction model includes a first prediction sub-model and a second prediction sub-model, wherein the first prediction sub-model and the second prediction sub-model predict in parallel. The first prediction sub-model is an autoregressive model based on time series analysis, which may be an autoregressive integral moving average model or a seasonal autoregressive model, used to capture the periodic and trend components of business traffic. Specifically, the data packet arrival sequence extracted from historical business traffic patterns and arranged in chronological order is input into the first prediction sub-model. Through integral or differential processing, the long-term upward or downward trend of business volume is identified and fitted. For the seasonal autoregressive model, by introducing seasonal parameters, the fixed periodic patterns that recur in business volume are explicitly modeled, and then the predicted business intensity values ​​for the next T time units are output and converted into the corresponding business occurrence probability sequence. The second prediction sub-model is a classification model based on a lightweight gradient booster. It iteratively trains multiple weak decision trees, each new tree working to correct the prediction error of the previous tree combination. Finally, the prediction results of all trees are weighted and summed to obtain a strong predictor, used to learn complex nonlinear patterns of business events. Specifically, the statistical and temporal characteristics of historical business sequences, the current time context information, and weighting factors are input into the second prediction sub-model, outputting a sequence of probability values ​​for business occurrence in each future time unit. A complex mapping relationship between features and labels is established; for example, when channel quality is good, it is at a historical peak, and it is a weekday, the business probability is extremely high. Finally, the output probabilities of the two sub-models are weighted and fused, with the weights dynamically adjusted based on historical sequence performance and the current prediction context, ultimately outputting an initial sequence of future business activity probabilities.

[0032] Step S300: Send the device power consumption policy of each communication device to the master control node, arbitrate the received device power consumption policy based on the global network status, generate the arbitrated policy instruction, send it to the corresponding communication device, and execute the arbitrated policy instruction to realize global low-power communication management.

[0033] Step S300 further includes step S310, identifying channel and resource contention relationships based on the device power consumption strategy; step S320, ranking the communication devices and their power consumption strategies that have a contention relationship according to the service priority rules; step S330, adjusting the power consumption strategies of the conflicting devices according to the ranking results and the global network status, wherein the adjustment includes allocating requested resources to the communication devices corresponding to high-priority services and modifying the power consumption strategies of low-priority devices, including delaying the service execution time, allocating alternative channels, or instructing them to enter a lower-power sleep mode; step S340, generating an arbitrated policy instruction based on the adjustment results and issuing it.

[0034] Preferably, the power consumption policies of each communication device are sent to the master control node. The master control node analyzes all reported power consumption policies to detect whether there are plans that would cause multiple devices to communicate at the same time using the same wireless resources, thus causing conflicts. Based on the global network status, the master control node arbitrates the received power consumption policies. Specifically, the master control node parses each device's policy into a resource occupancy plan table. Key parsed fields include the planned communication time window, requested channel / frequency band, transmit power level, and service type and data volume. Conflict detection is performed based on the parsed resource occupancy plan table, including channel-time conflicts, spatial-interference conflicts, and network resource conflicts. Channel-time conflicts check whether there is time overlap between the channels and time windows of different devices. If there is overlap, it is determined as direct channel contention. Spatial-interference conflicts refer to potential interference conflicts if devices use different channels but are geographically close and the high-power transmission of one device may cause co-channel or adjacent-channel interference to the reception of another device. Network resource conflicts check whether multiple devices plan to send a large amount of data to the same aggregation node in the same time period, which may cause buffer overflow or processing overload of that node.

[0035] Preferably, the service priority rules are used to sort the conflicting parties by importance to determine the priority of resource allocation. For example, absolute priority, emergency signaling / control instructions have the highest priority, real-time services have higher priority than non-real-time services, and guaranteed services have higher priority than best-effort services. Relative priority, the higher the criticality of the device, the higher the urgency of the service, the higher the priority, and services that can alleviate the load of hotspot areas have high priority. The master control node calculates a dynamic priority score for each conflicting communication device and the device power consumption strategy according to the service priority rules, and sorts all conflicting parties in descending order.

[0036] Preferably, based on the ranking results and the global network status, the master control node adjusts the power consumption strategy of conflicting devices to eliminate conflicts while ensuring the execution of high-priority strategies. The global network status may include the overall network topology and link quality, historical and real-time interference levels of each channel, and the overall network energy consumption distribution and hotspots. Adjustments include allocating requested resources to communication devices corresponding to high-priority services, i.e., confirming and locking the channel resources requested by high-priority devices in their strategies, prohibiting other devices from occupying them; and modifying the power consumption strategy of low-priority devices, including delaying service execution time, allocating alternative channels, or instructing them to enter a lower-power sleep state. The system employs several modes, including: Delaying service execution time involves issuing instructions to low-priority devices, commanding them to postpone planned communication activities to a specified time after the conflict period, overriding their local policy's wake-up and transmit time parameters; Assigning alternative channels assigns different, idle, or less-interference channels to low-priority devices, allowing them to change their original planned communication channels, requiring multi-channel switching capabilities; and Instructing entry into a lower-power sleep mode directly commands low-priority devices to enter a deeper sleep state than originally planned, or extends their sleep period, ensuring they won't wake up during the conflict and thus completely avoiding contention. Finally, an arbitrated policy instruction is generated based on the adjustment results. For high-priority devices that haven't been adjusted, the instruction may be a confirmation and execution order of their reported policy; for low-priority devices that have been adjusted, the instruction is an overriding instruction explicitly including the modified parameters. The master control node accurately sends the arbitrated policy instruction to each corresponding communication device via a reliable signaling link. Upon receiving the instruction, the communication device terminates its locally parsed original policy and unconditionally executes the arbitrated instruction issued by the master control node, achieving global low-power communication control.

[0037] Furthermore, step S340 also includes: when the first communication device establishes a main communication link with the master control node during arbitration due to high-priority services, the master control node identifies the estimated link margin of the main communication link; based on the estimated link margin, it schedules one or more second communication devices located in the vicinity of the first communication device that have non-urgent batch data to be transmitted; based on the first communication device and the second communication device, it generates a cooperative piggybacking instruction and sends it to the first communication device and the second communication device to load the communication tasks of the second communication device into the main communication link of the first communication device; wherein, when executing the cooperative piggybacking instruction, the strategy instruction of the first communication device is configured to reserve an auxiliary data field for the non-urgent batch data in the main communication frame transmitting its high-priority service data; the strategy instruction of the second communication device is configured to encapsulate the non-urgent batch data into the format defined by the auxiliary data field, and when the first communication device establishes the main communication link, it sends the encapsulated data to the first communication device or directly and synchronously to the master control node with an additional power lower than the power required for independent transmission, so as to complete the piggybacking transmission.

[0038] Preferably, when the first communication device establishes a main communication link with the master control node during arbitration due to high-priority services, the master control node calculates the estimated link margin of the main communication link based on physical layer margin, protocol layer margin, and power margin. Specifically, the data rate required by the high-priority service is much smaller than the maximum Shannon capacity that the link can support under the current channel conditions; the payload area of ​​the main communication protocol frame still has unused bit space remaining after allocating high-priority service data; and the transmit power allocated to the communication device to ensure the reliability of the high-priority service may be higher than its actual minimum required power. Then, based on the estimated link margin, suitable devices that can utilize this margin are selected, i.e., one or more second communication devices located in the vicinity of the first communication device and having non-urgent batch data to transmit are scheduled. These second communication devices must be located in the vicinity of the first communication device, possess non-urgent batch data to be transmitted, and have channel quality between themselves and the first device or the master control node that allows for reliable low-power transmission.

[0039] Preferably, based on the first communication device and the second communication device, the master control node generates a collaborative piggybacking instruction, including instructions to the first communication device and instructions to the second communication device. Specifically, the master control node instructs the first communication device to reserve an auxiliary data field with a specific format and position in its main communication frame constructed for high-priority services to carry piggyback data. At the same time, the master control node explicitly informs the first communication device of the start position, length, and modulation and coding scheme of the auxiliary field. During transmission, the master control node does not encode or process the content of the auxiliary field, but transmits it as a transparent payload and then sends it down to the first and second communication devices to load the communication tasks of the second communication device into the main communication link of the first communication device. The first communication device transmits its own high-priority data with extremely low marginal energy consumption for transmitting additional bits. It then instructs the second communication device to encapsulate its non-urgent batch data according to the format specified in the instructions, including adding simplified frame headers and CRC, ensuring the data block format matches the reserved fields. The second communication device is then instructed to perform relay piggyback transmission or direct piggyback transmission. In relay piggyback transmission, the second communication device transmits the encapsulated data to the first communication device at a very low additional power at the same time or precisely at the same time the first communication device transmits the main communication frame, and then transmits the superimposed data to the master node. In direct piggyback transmission, the second communication device transmits its data directly and synchronously to the master node at very low additional power. The master node simultaneously receives both signals from the first and second communication devices and processes them collaboratively. This process ultimately completes the piggyback transmission while significantly reducing energy consumption.

[0040] Furthermore, step S300 also includes step S350, if the policy instruction indicates entering or maintaining a sleep mode, then the communication device shuts down the main communication module and starts a low-power keep-alive heartbeat mechanism with an extended cycle; step S360, if the policy instruction indicates entering or maintaining a working mode, then the communication device performs communication configuration according to the connection method, transmission power level and heartbeat cycle parameters specified in the instruction.

[0041] Preferably, the arbitration-tried policy instruction is sent to the corresponding communication device for execution. If the policy instruction indicates entering or maintaining a sleep mode, the communication device shuts down the main communication module, that is, shuts down the device's main communication RF front-end and its related baseband processing unit, cuts off the power supply to the RF power amplifier, transceiver chip, and high-speed ADC / DAC, or puts them into a deep power-down state. In this state, the device cannot receive or send any service data. At the same time, only a very low-power timer and a very simple secondary communication module are kept powered by a weak amount of power. Specifically, after the device enters sleep mode, the main CPU and main communication module are completely shut down, and the low-power timer starts counting down. When the timer expires, a hardware interrupt is triggered, instantly waking up the main CPU and secondary communication module. The awakened device sends a very short keep-alive heartbeat data packet to the master control node through the secondary communication module, containing only the device ID and status code. After sending, the device immediately shuts down the main CPU and main communication module again, resets the timer, and enters the next sleep cycle. The heartbeat cycle in sleep mode is much longer than the heartbeat cycle in working mode, thereby significantly reducing the average power consumption.

[0042] Preferably, if the policy instruction indicates entering or maintaining a working mode, i.e. waking up from a dormant state or remaining in an active state, the communication device establishes a communication connection and prepares for service transmission according to the connection method, transmit power level, and heartbeat cycle parameters specified in the instruction. The connection method instruction explicitly specifies the network node, network protocol, and wireless access parameters for the connection established by the device. The transmit power level instruction specifies a discrete power level index or a precise transmit power value. The heartbeat cycle parameter instruction specifies the time interval for the device to send a keep-alive heartbeat to the master control node in the working state. Specifically, when the communication device is awakened from dormancy, the main communication module is powered on, the protocol stack is initialized, a network layer connection is established according to the connection method specified in the instruction, the RF transmit power is set to the transmit power level specified in the instruction, and the internal heartbeat timer is set to the heartbeat cycle parameters specified in the instruction. The device enters a ready state and can begin transmitting its own high-priority services or wait to execute other collaborative tasks, thereby achieving precise control of global low-power communication.

[0043] Furthermore, step S350 also includes the following: the triggering condition for the low-power keep-alive heartbeat mechanism with extended startup cycle is that the communication device is detected by the master node to be in an idle state for a duration exceeding a first preset threshold.

[0044] Preferably, when the master control node detects that the communication device is in an idle state for a duration exceeding a first preset threshold, a low-power keep-alive heartbeat mechanism with an extended cycle is initiated. The idle state of the communication device may include no service session data, no resource occupation, maintaining network layer connection but no effective payload transmission, and not being assigned to execute collaborative tasks. The master control node comprehensively judges whether the device is in an idle state by parsing the heartbeat packets reported by the device, the source address of the service data packets, and the allocation records of the resource scheduler. The first preset threshold is a configurable time parameter used to determine whether the communication device has entered a stable idle state that can safely hibernate, avoiding accidental triggering of hibernation due to short-term interruptions in service flow, such as the silence period in a voice call or the processing delay between data packets, which could lead to service interruption or frequent state switching.

[0045] Furthermore, step S350 also includes: identifying a communication device that is about to enter or is currently in an idle listening state; distributing a collaborative sensing instruction to control the communication device to enter an idle state and perform a collaborative sensing task; based on the communication device corresponding to the collaborative sensing instruction, performing local signal processing on the received radio frequency signal to detect whether there are target signal features; the communication device encapsulates the detection result into simplified sensing data and reports it along with the main business data when it next performs business communication or heartbeat reporting to the master control node.

[0046] Preferably, the master control node identifies communication devices that will enter an idle listening state according to the global scheduling plan, that is, it is known that a certain communication device will have a planned idle waiting time before the next scheduling cycle arrives after completing the current task; it also identifies communication devices that are currently in an idle listening state, that is, they meet the hibernation trigger conditions but the master control node, for some strategy, does not instruct them to enter deep hibernation, but keeps them in a shallow hibernation or idle listening state; then the master control node sends a cooperative sensing command to the identified communication device to control the communication device to enter an idle state to execute a cooperative sensing task. The command content includes sensing task ID, target frequency band, scanning time window, signal acquisition duration, sampling rate and other sensing parameters, target signal feature description and local processing parameters.

[0047] Preferably, the communication device based on the collaborative sensing command tunes its RF front-end to a specified frequency band according to the command parameters. Within a specified time window, it activates the ADC to sample RF signals, acquires the RF signals, and performs local signal processing, including calculating the change in received signal strength over time to determine if any signals exceeding a threshold appear; generating a spectrum through a Fast Fourier Transform to detect the presence of energy peaks at specific frequency points; performing a sliding correlation operation between the received signal and the target signal feature template provided in the command to find matching peaks; and further detecting the presence of target signal features. Finally, the communication device encapsulates the detection results into simplified sensing data, and in the next business communication or heartbeat reporting to the master node, the simplified sensing data is reported as an auxiliary information field along with the main business data. This reuses the idle time, idle RF receiver chain, and idle processing capacity of the communication device for sensing tasks, maximizing the utilization of hardware resources and minimizing the impact on the overall network's energy consumption budget.

[0048] In the above text, refer to Figure 1 A low-power communication method under a private communication network according to embodiments of the present invention is described in detail. Next, reference will be made to... Figure 2 A low-power communication device for a private communication network according to an embodiment of the present invention is described.

[0049] The low-power communication device for a private communication network according to embodiments of the present invention addresses the technical problem in existing multi-device private communication networks where the lack of globally coordinated dynamic power consumption management leads to conflicts between local energy saving and global network performance, resulting in suboptimal overall energy efficiency. It achieves the technical effect of ensuring network service quality while realizing dynamic optimization and balance of network-level energy consumption, thereby improving overall communication energy efficiency and sustainable operation capabilities. Figure 2 As shown, the low-power communication device under the private communication network includes: a device status information acquisition module 10, a power consumption policy parsing module 20, and a policy instruction generation module 30.

[0050] The device status information acquisition module 10 is used to acquire multi-dimensional status information of communication devices, including at least historical service traffic patterns, remaining device power, and current channel quality. The power consumption policy parsing module 20 is used to parse the power consumption policy based on the multi-dimensional status information to determine the device power consumption policy, which is a management policy to achieve low power consumption for the device itself. The policy instruction generation module 30 is used to send the device power consumption policies of each communication device to the master control node, arbitrate the received device power consumption policies based on the global network status, generate arbitrated policy instructions, send them to the corresponding communication devices, and execute the arbitrated policy instructions to achieve global low-power communication control.

[0051] The specific configuration of the power consumption strategy parsing module 20 will be described in detail below. The power consumption strategy parsing module 20 further includes: predicting the probability distribution of the service activity of the communication device in a future period based on historical service traffic patterns and current channel quality, and generating a service activity probability curve; matching the service activity probability curve with multiple preset benchmark power consumption patterns, whereby the benchmark power consumption patterns define benchmark configurations for sleep levels, wake-up periods, and transmit power under different service scenarios; optimizing the matched benchmark configurations by combining the remaining battery power of the device with the goal of minimizing local power consumption, and generating a device power consumption strategy that includes specific sleep duration and transmit power levels.

[0052] The specific configuration of the power consumption strategy analysis module 20 will be described in detail below. The power consumption strategy analysis module 20 further includes: extracting historical service traffic patterns, describing the number of data packets arriving or the interval of communication events recorded in a time sequence, and extracting the temporal characteristics of the historical service traffic patterns, including periodic characteristics, statistical characteristics, and recent trends; obtaining current channel quality indicators, including signal-to-noise ratio and signal received strength, quantifying the current channel quality indicators into weighting factors affecting transmission reliability, and characterizing the signal state coefficients representing the reliability of the current transmission link; inputting the extracted temporal characteristics, the current time context information, and the weighting factors into a prediction model, and outputting the probability values ​​of service communication occurring within the next T time units; constructing a discrete-time probability sequence from the probability values ​​of service communication occurring within the next T time units; and smoothing the discrete-time probability sequence to construct a continuous or segmented continuous service activity probability curve.

[0053] The specific configuration of the power consumption strategy parsing module 20 will be described in detail below. The power consumption strategy parsing module 20 further includes: the prediction model consists of a first prediction sub-model and a second prediction sub-model in parallel; wherein, the first prediction sub-model is an autoregressive model based on time series analysis, used to capture the periodic and trend components of business traffic; the second prediction sub-model is a classification model based on a lightweight gradient boosting machine, used to learn the complex nonlinear patterns of business event occurrences; this layer performs weighted fusion of the output probabilities of the two sub-models to generate an initial future business activity probability sequence.

[0054] The specific configuration of the policy instruction generation module 30 will be described in detail below. The policy instruction generation module 30 further includes: identifying channel and resource contention relationships based on the device power consumption policy; ranking communication devices and their power consumption policies that are in contention according to service priority rules; adjusting the power consumption policies of conflicting devices based on the ranking results and the global network status, wherein the adjustment includes allocating requested resources to communication devices corresponding to high-priority services and modifying the power consumption policies of low-priority devices, including delaying service execution time, allocating alternative channels, or instructing them to enter a lower-power sleep mode; and generating and issuing arbitrated policy instructions based on the adjustment results.

[0055] The specific configuration of the policy instruction generation module 30 will be described in detail below. The strategy instruction generation module 30 further includes: when the first communication device establishes a main communication link with the master control node due to high-priority services during arbitration, the master control node identifies the estimated link margin of the main communication link; based on the estimated link margin, it schedules one or more second communication devices located in the vicinity of the first communication device and waiting to transmit non-urgent batch data; based on the first communication device and the second communication device, it generates a cooperative piggyback instruction and sends it to the first communication device and the second communication device to load the communication tasks of the second communication device into the main communication link of the first communication device; wherein, when executing the cooperative piggyback instruction, the strategy instruction of the first communication device is configured to reserve an auxiliary data field for the non-urgent batch data in the main communication frame transmitting its high-priority service data; the strategy instruction of the second communication device is configured to encapsulate the non-urgent batch data into the format defined by the auxiliary data field, and when the first communication device establishes the main communication link, it sends the encapsulated data to the first communication device or directly and synchronously to the master control node with an additional power lower than the power required for independent transmission to complete the piggyback transmission.

[0056] The specific configuration of the policy instruction generation module 30 will be described in detail below. The policy instruction generation module 30 further includes: if the policy instruction indicates entering or maintaining a sleep mode, the communication device shuts down the main communication module and initiates a low-power keep-alive heartbeat mechanism with an extended cycle; if the policy instruction indicates entering or maintaining a working mode, the communication device performs communication configuration according to the connection method, transmission power level, and heartbeat cycle parameters specified in the instruction.

[0057] The specific configuration of the policy instruction generation module 30 will be described in detail below. The policy instruction generation module 30 further includes: the triggering condition for the low-power keep-alive heartbeat mechanism with extended startup cycle is that the communication device is detected by the master node to be in an idle state for a duration exceeding a first preset threshold.

[0058] The specific configuration of the policy instruction generation module 30 will be described in detail below. The policy instruction generation module 30 further includes: identifying communication devices that are about to enter or are currently in an idle listening state; distributing cooperative sensing instructions to control the communication devices to enter an idle state and perform cooperative sensing tasks; based on the communication device corresponding to the cooperative sensing instructions, performing local signal processing on the received radio frequency signals to detect the presence of target signal characteristics; the communication device encapsulating the detection results into simplified sensing data and reporting it along with the main service data during the next business communication or heartbeat reporting to the master control node.

[0059] The low-power communication device under a private communication network provided in the embodiments of the present invention can execute the low-power communication method under a private communication network provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0060] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A low-power communication method under a private communication network, characterized in that, include: Collect multi-dimensional status information of communication equipment, including at least historical service traffic patterns, remaining battery power, and current channel quality; Based on the multi-dimensional state information, power consumption strategy is analyzed to determine the device power consumption strategy, which is a management strategy to achieve low power consumption of the device itself. The device power consumption policies of each communication device are sent to the master control node. The received device power consumption policies are arbitrated based on the global network status to generate arbitrated policy instructions, which are then sent to the corresponding communication devices. The arbitrated policy instructions are executed to achieve global low-power communication management.

2. The low-power communication method under a private communication network according to claim 1, characterized in that, Based on the multi-dimensional state information, power consumption strategy analysis is performed to determine the device power consumption strategy, including: Based on historical traffic patterns and current channel quality, predict the probability distribution of the service activity of the communication device in the next period and generate a service activity probability curve. The business activity probability curve is matched with multiple preset benchmark power consumption modes, which define the benchmark configuration of sleep level, wake-up cycle and transmit power under different business scenarios. With the goal of minimizing local power consumption, the parameters of the matching baseline configuration are optimized based on the remaining power of the device to generate the device power consumption strategy, which includes specific sleep duration and transmit power level.

3. The low-power communication method under a private communication network according to claim 2, characterized in that, Generate a business activity probability curve, including: Extract historical service traffic patterns, describe the number of data packets arriving or the interval of communication events recorded in time series, and extract the time series characteristics of historical service traffic patterns, including periodic characteristics, statistical characteristics and recent trends. Obtain current channel quality indicators, including signal-to-noise ratio and signal received strength, quantify the current channel quality indicators into weighting factors that affect transmission reliability, and characterize the signal state coefficients that represent the reliability of the current transmission link. The extracted temporal features, the current time context information, and the weighting factors are input into the prediction model, which outputs the probability value of business communication occurring within the next T time units. The probability values ​​of business communication occurring within the next T time units are used to construct a discrete-time probability sequence; The discrete-time probability sequence is smoothed to construct a continuous or segmented continuous business activity probability curve.

4. The low-power communication method under a private communication network according to claim 3, characterized in that, The prediction model consists of a first prediction sub-model and a second prediction sub-model in parallel. The first prediction sub-model is an autoregressive model based on time series analysis, used to capture the periodic and trend components of business traffic. The second prediction sub-model is a classification model based on a lightweight gradient booster, used to learn the complex nonlinear patterns of business events. This layer performs weighted fusion of the output probabilities of the two sub-models to generate an initial sequence of future business activity probabilities.

5. The low-power communication method under a private communication network according to claim 2, characterized in that, Arbitrate the received device power consumption policy based on the global network state to generate an arbitrated policy instruction, including: Identify channel and resource contention relationships based on the device power consumption strategy; Based on the business priority rules, the communication devices and their power consumption strategies that are in competition are sorted. Based on the ranking results and the global network status, the power consumption strategy of the conflicting devices is adjusted. The adjustment includes allocating request resources to the communication devices corresponding to high-priority services and modifying the power consumption strategy of low-priority devices. The modification includes delaying the service execution time, allocating alternative channels, or instructing them to enter a lower-power sleep mode. Based on the adjustment results, generate and issue the arbitrated strategy instructions.

6. The low-power communication method under a private communication network according to claim 5, characterized in that, The generated policy instructions after arbitration also include: When the first communication device establishes a main communication link with the master control node due to high-priority services during arbitration, the master control node identifies the estimated link margin of the main communication link. Based on the estimated link margin, schedule one or more second communication devices located in the vicinity of the first communication device that are waiting to transmit non-urgent batch data. Based on the first communication device and the second communication device, a collaborative piggyback instruction is generated and sent to the first communication device and the second communication device to load the communication task of the second communication device into the main communication link of the first communication device; Specifically, the coordinated piggybacking instruction is executed to configure the policy instruction of the first communication device to reserve an auxiliary data field for the non-urgent batch data in the main communication frame that transmits its high-priority service data; The second communication device is configured to encapsulate non-urgent batch data into the format defined by the auxiliary data field, and when the first communication device establishes the main communication link, the encapsulated data is sent to the first communication device or directly and synchronously to the master control node with an additional power lower than that required for independent transmission, so as to complete the piggyback transmission.

7. The low-power communication method under a private communication network according to claim 5, characterized in that, Send to the corresponding communication device to execute the arbitration-adjusted policy instructions, including: If the policy instruction indicates to enter or remain in sleep mode, the communication device shuts down the main communication module and initiates a low-power keep-alive heartbeat mechanism with extended cycle. If the policy instruction indicates to enter or maintain the working mode, the communication device performs communication configuration according to the connection method, transmission power level and heartbeat cycle parameters specified in the instruction.

8. The low-power communication method under a private communication network according to claim 7, characterized in that, The trigger condition for the low-power keep-alive heartbeat mechanism with extended startup cycle is that the communication device is detected by the master node to be in an idle state for a duration exceeding a first preset threshold.

9. The low-power communication method under a private communication network according to claim 8, characterized in that, Also includes: Identify communication devices that are about to enter or are currently in an idle listening state, and distribute cooperative sensing instructions to control the communication devices to enter an idle state to perform cooperative sensing tasks; Based on the communication device corresponding to the cooperative sensing instruction, the received radio frequency signal is processed locally to detect whether target signal features exist. The communication device encapsulates the detection results into simplified sensing data and reports it along with the main business data during the next business communication or heartbeat reporting to the master control node.

10. A low-power communication device under a private communication network, characterized in that, The apparatus is used to implement the low-power communication method under a private communication network as described in any one of claims 1 to 9, and the apparatus comprises: The device status information acquisition module is used to collect multi-dimensional status information of the communication device, which includes at least historical service traffic patterns, remaining battery power, and current channel quality. The power consumption strategy parsing module is used to parse the power consumption strategy based on the multi-dimensional state information and determine the device power consumption strategy, which is a management strategy to achieve low power consumption of the device itself. The policy instruction generation module is used to send the device power consumption policies of each communication device to the master control node, arbitrate the received device power consumption policies based on the global network status, generate arbitrated policy instructions, send them to the corresponding communication devices, and execute the arbitrated policy instructions to realize global low-power communication management.

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