Wireless sensor transmission scheduling method and system suitable for self-energy-taking scene

Abstract

The invention relates to a wireless sensor transmission scheduling method and system suitable for a self-energy-taking scene, and belongs to the technical field of wireless sensor communication. Comprising the following steps: establishing a point-to-point communication model taking a time slot as a unit based on a wireless sensor and gateway equipment, and obtaining uplink and downlink channel gains through testing; calculating an energy value collected in each time slot and an energy value consumed by sending data once meeting the minimum transmission rate requirement in combination with the transmitting power of the gateway equipment and the environmental noise; discretizing the energy storage capacity of the wireless sensor into multiple energy levels, and discretizing an energy value collected by the wireless sensor in each time slot and an energy value consumed by sending data once based on a discrete energy level model; at the beginning of each time slot, reading the residual energy of the wireless sensor and an energy value consumed by discretized data transmission once; according to a preset criterion rule, determining an action type executed by the wireless sensor in the current time slot; data sending or energy charging can be autonomously determined to be executed, and the energy utilization rate is optimized.

Description

Technical Field

[0001] This invention relates to a wireless sensor transmission scheduling method and system suitable for self-powered scenarios, belonging to the field of wireless sensor communication technology. Background Technology

[0002] In special scenarios such as power transmission lines in mountainous areas and ecological monitoring in the wild, massive numbers of sensors cannot be continuously powered by mains electricity. Traditional batteries also have limited capacity and require frequent replacement, which can easily lead to data interruptions and functional failures. To address this, self-powered technology has been widely used, enabling long-term power supply and significantly reducing maintenance costs. However, existing self-powered communication systems lack a mechanism to dynamically optimize transmission behavior based on remaining energy. Traditional low-power sensor networks aim to increase the sleep rate and reduce power consumption, but their fixed-period communication method is difficult to adapt to the random fluctuations in self-powered energy. That is, when the energy is too low, transmission interruptions are likely to occur, and when the energy is sufficient, energy may be wasted due to failure to send data in a timely manner, failing to achieve an optimal balance between energy utilization and communication performance.

[0003] For example, Chinese invention patent application CN119277421A discloses an energy control method and system for wireless sensor networks, including the following steps: acquiring the operating status and state transition time of multiple wireless sensors in the wireless sensor network; inputting the operating status and state transition time into a pre-built energy consumption prediction model to obtain the energy consumption prediction result output by the energy consumption prediction model; determining data quality requirements and evaluating data acquisition requirements based on the energy consumption prediction result to obtain the operating requirement evaluation result; dynamically adjusting the sleep cycle and data transmission parameters of multiple wireless sensors based on the operating requirement evaluation result; monitoring the adjusted energy consumption level of multiple wireless sensors, identifying abnormal nodes, and adjusting the connection path of multiple wireless sensors; however, when calculating the optimal path, it needs to acquire high-frequency data such as the communication quality and current load of all nodes in real time, which will increase additional energy consumption.

[0004] For example, Korean invention patent application KR101396836B1 discloses a method and system for controlling contactless power supply to a wireless sensor network, including the steps of: monitoring the energy status of the wireless sensor network, and controlling the wireless sensor network to wirelessly supply power when it is detected that the wireless sensor network needs power. Therefore, power can be supplied to the wireless sensor network based on wireless power transmission only when needed, thereby minimizing energy consumption and sending power supply control messages only when required. However, it does not involve specific adjustment algorithms or threshold standards for the coordinator node's dynamic adjustment of state transition times, and does not design any related triggering mechanisms.

[0005] In summary, there is an urgent need for a wireless sensor transmission scheduling method and system that can dynamically optimize transmission behavior based on remaining energy, adapt to random fluctuations in self-harvested energy, and achieve an optimal balance between energy utilization and communication performance. Summary of the Invention

[0006] To address the problems existing in the prior art, this invention proposes a wireless sensor transmission scheduling method and system suitable for self-powered scenarios.

[0007] The technical solution of the present invention is as follows: On the one hand, this invention proposes a wireless sensor transmission scheduling method suitable for self-powered scenarios, comprising the following steps: A point-to-point wireless communication model is constructed based on the operating characteristics of the point-to-point wireless communication system. The point-to-point wireless communication model performs data transmission and energy harvesting activities according to the preset single time slot action rules, and obtains the operating status characteristic parameters of the wireless sensor, including real-time energy value, transmission energy consumption and channel gain. The point-to-point wireless communication system consists of a gateway device and a wireless sensor. Based on the operating state characteristic parameters and the energy storage capacity of the wireless sensor, a discrete energy level model is constructed. The discrete energy level model divides the energy storage state into several energy levels and establishes the correspondence between each energy level and the remaining energy. At the beginning of each time slot, the remaining energy corresponding to the current energy level of the wireless sensor is obtained based on the discrete energy level model. The remaining energy is compared with the energy consumption threshold, and a scheduling decision is executed according to the comparison result and the preset scheduling rules. Record the throughput of the current time slot after executing the scheduling decision, calculate the system average throughput based on the throughput of each time slot, and optimize the preset scheduling rules based on the system average throughput.

[0008] Preferably, the single-slot action rule specifically means that in each time slot, the wireless sensor performs one action: energy harvesting or data transmission.

[0009] Preferably, the real-time energy value in the operating state characteristic parameters is expressed by the formula: ; In the formula, This represents the energy value collected by the wireless sensor in each time slot. Indicates energy conversion efficiency. Indicates downlink power gain. This indicates the fixed transmit power of the gateway device.

[0010] Preferably, the energy consumption threshold is the discretized minimum transmission energy consumption that satisfies the minimum transmission rate, expressed by the formula: ; ; In the formula, Indicates the minimum transmission rate. This indicates the minimum power consumption required for a wireless sensor to meet the minimum transmission rate. Indicates uplink power gain. This represents the noise power of Gaussian white noise in the environment. This represents the minimum transmission energy consumption that satisfies the minimum transmission rate after discretization. Indicates that the wireless sensor is in the first position. The remaining energy at each energy level This means finding the condition in all energy levels. The smallest energy level that can be established , This indicates that the wireless sensor is in the first position. The remaining energy at each energy level.

[0011] Preferably, the discrete energy level model is expressed by the following formula: ; In the formula, For energy level indexing, Indicates that the wireless sensor is in the first position. The remaining energy at each energy level Indicates the energy storage capacity of the wireless sensor. This indicates the number of discrete energy levels.

[0012] Preferably, the preset scheduling rule is expressed by the following formula: ; In the formula, Indicates the wireless sensor in the time slot real-time scheduling decisions Indicates energy harvesting operation. Indicates a data transfer operation. Indicates in time slot The remaining energy in the energy storage device of the wireless sensor.

[0013] Preferably, the throughput of the current time slot is recorded after the scheduling decision is executed, and the average system throughput is calculated based on the throughput of each time slot, expressed by the formula:

[0014] ; In the formula, This represents the average data throughput of the wireless sensor transmission scheduling system. Indicates the minimum transmission rate. Represents probability. This represents the minimum transmission energy consumption that satisfies the minimum transmission rate after discretization. This indicates the remaining energy in the energy storage device of the wireless sensor. To express summation, Indicates the number of discrete energy levels. Indicates the energy storage capacity of the wireless sensor. Indicates that the wireless sensor is in the first position. The steady-state probability at each energy level This represents the minimum signal-to-noise ratio achieved by the gateway device signal to achieve the minimum transmission rate. This represents the noise power of Gaussian white noise in the environment. Indicates taking Exponentiation, Indicates the total downlink wireless power transfer channel gain. The average value, Represents the variable to be summed. Indicates the number of antennas. It represents factorial.

[0015] Preferably, the steady-state probability is expressed by the formula: ; in: ; ; ; In the formula, Indicates that the wireless sensor is in the first position. The steady-state probability at each energy level Represents the energy conversion matrix. Represents the transpose of a matrix. express A matrix of order all 1s, express An identity matrix of order 1. Represents the rows of a matrix. Represents the columns of a matrix; express A unit column vector of order 1.

[0016] Preferably, the energy conversion matrix is ​​expressed by the formula: ; In the formula, Represents the energy conversion matrix. This represents the probability that the energy level of the energy storage device in a wireless sensor is initially 0, and remains 0 after one time slot. This indicates that the energy level of the energy storage device in the wireless sensor changes from 0 to 1 within a time slot. The probability, This indicates that the energy level of the energy storage device in the wireless sensor changes from 0 to a certain value within one time slot. The probability, This indicates that the energy level of the energy storage device in the wireless sensor at the beginning of a time slot is... It remains at the end of the time slot. The probability, This indicates that the energy level of the energy storage device in the wireless sensor changes from a certain value within a time slot. Switch to The probability, This indicates that the energy level of the energy storage device in the wireless sensor changes from a certain value within a time slot. Switch to The probability, This indicates that the energy level of the energy storage device in the wireless sensor remains unchanged. The probability remains unchanged; This indicates that the energy level of the energy storage device in the wireless sensor changes from a certain value within a time slot. Switch to The probability of.

[0017] On the other hand, the present invention also proposes a wireless sensor transmission scheduling system suitable for self-powered scenarios, comprising the following modules: Communication system initialization module: Based on the operating characteristics of the point-to-point wireless communication system, a point-to-point wireless communication model is constructed. The point-to-point wireless communication model performs data transmission and energy harvesting activities according to the preset single time slot action rules, and obtains the operating status characteristic parameters of the wireless sensor, including real-time energy value, transmission energy consumption and channel gain. The point-to-point wireless communication system consists of a gateway device and a wireless sensor. Discrete energy level model building module: Based on the operating state characteristic parameters and the energy storage capacity of the wireless sensor, a discrete energy level model is constructed. The discrete energy level model divides the energy storage state into several energy levels and establishes the correspondence between each energy level and the remaining energy. State scheduling module: At the beginning of each time slot, the remaining energy corresponding to the current energy level of the wireless sensor is obtained based on the discrete energy level model. The remaining energy is compared with the energy consumption threshold, and scheduling decisions are executed according to the comparison results and preset scheduling rules. Scheduling optimization module: Records the throughput of the current time slot after executing the scheduling decision, calculates the system average throughput based on the throughput of each time slot, and optimizes the preset scheduling rules based on the system average throughput.

[0018] The present invention has the following beneficial effects: (1) This invention is a wireless sensor transmission scheduling method and system applicable to self-powered scenarios. By establishing a discrete energy level model, it realizes the fine characterization and management of the energy storage state of wireless sensors. By discretizing the continuous energy collection value and energy consumption value into energy level units that match the energy storage capacity, the system can operate in a finite and deterministic state, laying the foundation for subsequent performance analysis based on probabilistic models.

[0019] (2) This invention is a wireless sensor transmission scheduling method and system applicable to self-powered scenarios. By using the criteria rule of real-time remaining energy and discretized energy consumption value, the scheduling method achieves simplicity and reliability. This rule does not require complex calculations. At the beginning of each time slot, it is only necessary to compare whether the current remaining energy is higher than the discretized energy consumption threshold required to transmit data, and then immediately make a decision on whether to collect energy or transmit data. This low-complexity online decision-making mechanism greatly reduces the computational overhead and execution cost of wireless sensor nodes, enabling them to quickly respond to changes in channel and energy status and ensure the stable operation of the system.

[0020] (3) This invention provides a wireless sensor transmission scheduling method and system suitable for self-powered scenarios. By constructing a complete performance analysis module, it achieves accurate quantitative evaluation of the system's average data throughput. Based on the discrete energy level model and scheduling strategy, this module derives the transition probabilities between energy states and further calculates the steady-state probability of the system in each state, thus ultimately providing a closed-form expression for the average throughput. This analytical framework enables designers to theoretically predict and optimize system performance before actual deployment. Attached Figure Description

[0021] Figure 1 This is a flowchart of the transmission scheduling method provided in Embodiment 1 of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] It should be understood that the step numbers used in the text are for ease of description only and are not intended to limit the order in which the steps are performed.

[0024] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0025] The terms “comprising” and “including” indicate the presence of the described feature, whole, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0026] The term “and / or” refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes these combinations.

[0027] Example 1: See Figure 1 This embodiment proposes a wireless sensor transmission scheduling method suitable for self-powered scenarios, including the following steps: S100. Establish a point-to-point communication system based on time slots. Construct a point-to-point wireless communication model based on the operating characteristics of the point-to-point wireless communication system. The point-to-point wireless communication model performs data transmission and energy harvesting activities according to preset single time slot action rules to obtain the operating status characteristic parameters of the wireless sensor, including real-time energy value, transmission energy consumption and channel gain. The point-to-point wireless communication system consists of a gateway device and a wireless sensor. It should be noted that the gateway device is equipped with multiple antennas, the number of which is... ; when hour, Indicates uplink power gain. Indicates downlink power gain; when When, use This represents the total uplink wireless data transmission channel gain. This represents the total downlink wireless power transmission channel gain; where, , ; It should be noted that the single-slot action rule specifically refers to the wireless sensor performing one action in energy harvesting or data transmission within each time slot.

[0028] S101. Based on the independent and identically distributed channel gain in both the same and different time slots, and the transmit power of the gateway device, calculate the real-time energy value in the operating state characteristic parameters, expressed by the formula: ; In the formula, This represents the energy value collected by the wireless sensor in each time slot. Indicates energy conversion efficiency. Indicates downlink power gain. This indicates the fixed transmit power of the gateway device.

[0029] S200. Based on the operating state characteristic parameters and the energy storage capacity of the wireless sensor, a discrete energy level model is constructed, expressed by the formula: ; In the formula, For energy level indexing, Indicates that the wireless sensor is in the first position. The remaining energy at each energy level Indicates the energy storage capacity of the wireless sensor. Indicates the number of discrete energy levels; It should be noted that the discrete energy level model divides the energy storage state into several energy levels and establishes a correspondence between each energy level and the remaining energy.

[0030] S300. Based on the discrete energy level model, the energy value collected by the wireless sensor in each time slot is discretized, expressed by the formula: ; In the formula, This represents the energy value collected by the discretized wireless sensor in each time slot. Indicates that the wireless sensor is in the first position. The remaining energy at each energy level , Indicates energy level index, This indicates the operation of finding the maximum value. Indicates that the wireless sensor is in the first position. The remaining energy at each energy level This represents the energy value collected by the wireless sensor in each time slot. Indicates the number of energy levels; Based on the discrete energy level model, the minimum transmission energy consumption that satisfies the minimum transmission rate after discretization, i.e., the energy consumption threshold, is calculated and expressed by the formula: ; ; In the formula, Indicates the minimum transmission rate. This indicates the minimum power consumption required for a wireless sensor to meet the minimum transmission rate. Indicates uplink power gain. This represents the noise power of Gaussian white noise in the environment. This represents the minimum transmission energy consumption that satisfies the minimum transmission rate after discretization. Indicates that the wireless sensor is in the first position. The remaining energy at each energy level This means finding the condition in all energy levels. The smallest energy level that can be established , This indicates that the wireless sensor is in the first position. The remaining energy at each energy level; It should be noted that the minimum transmission rate This can be expressed as a formula: ; In the formula, This indicates the minimum power consumption required for a wireless sensor to meet the minimum transmission rate. Indicates uplink power gain. This represents the noise power of Gaussian white noise in the environment.

[0031] S300. Compare the remaining energy with the energy consumption threshold, and execute a scheduling decision based on the comparison result and preset scheduling rules. Specifically: The preset scheduling rule is expressed by the following formula: ; In the formula, Indicates the wireless sensor in the time slot real-time scheduling decisions Indicates energy harvesting operation. Indicates a data transfer operation. Indicates in time slot The remaining energy in the energy storage device of the wireless sensor; It should be noted that at the beginning of each time slot, the criterion is that when the remaining energy is lower than the energy required for transmission, the wireless sensor is in energy harvesting mode to replenish energy; otherwise, it is in data transmission mode, consuming energy to transmit data. The current time slot is obtained after executing the scheduling decision. The throughput at the location.

[0032] S400, Record the current time slot after executing the scheduling decision. The throughput at that location is expressed by the formula: ; In the formula, Indicates in time slot Data throughput of wireless sensors at that location. Indicates in time slot The remaining energy in the energy storage device of the wireless sensor. This represents the minimum transmission energy consumption that satisfies the minimum transmission rate after discretization. This indicates the minimum transmission rate.

[0033] Furthermore, after time slots Afterwards, At each time slot, the remaining energy of the energy storage device in the wireless sensor is expressed by the formula: ; In the formula, Indicates in time slot The remaining energy in the energy storage device of the wireless sensor. This indicates the energy storage capacity of the wireless sensor.

[0034] S401. Based on the possible actions of the wireless sensor in each time slot, the energy state transition is divided into 8 cases, and the probability of energy level transition in each time slot is calculated. Specifically: A1、 This indicates that the initial energy level of the energy storage device in the wireless sensor is 0, and the energy level remains 0 after one time slot; that is, the current channel conditions are poor, and the charging capacity in one time slot is insufficient to complete one energy level transition. The probability of energy level transition is expressed by the formula: ; ; In the formula, This represents the probability that the energy level of the energy storage device in a wireless sensor is initially 0, and remains 0 after one time slot. Represents probability. This represents the energy value collected by the discretized wireless sensor in each time slot. Indicates energy conversion efficiency. Indicates the total downlink wireless power transmission channel gain. Indicates the energy storage capacity of the wireless sensor. Indicates the number of discrete energy levels. Indicates the transmit power of the gateway device. Indicates taking Exponentiation, Represents the variable to be summed. Indicates the number of antennas. To represent factorial, Indicates from arrive Perform summation; Indicates the total downlink wireless power transfer channel gain. The average value, Indicates the distance between the wireless sensor and the gateway device. Indicates path loss; A2, The probability of an energy level transition from 0 to L within a time slot in a wireless sensor's energy storage device is expressed by the formula: ; In the formula, This indicates that the energy level of the energy storage device in the wireless sensor changes from 0 to 1 within a time slot. The probability of; A3 ,in This indicates that the energy storage device in the wireless sensor has undergone a charging process, but the battery is not fully charged. In and The probability of energy level transition between them can be expressed by the formula:

[0035] ; In the formula, This indicates that the energy level of the energy storage device in the wireless sensor changes from 0 to a certain value within one time slot. The probability of; A4 ,in This indicates that the energy level of the energy storage device in the wireless sensor is at the beginning of a time slot. It remains at the end of the time slot. This means that the remaining energy is insufficient to transmit energy for charging, but due to poor channel conditions, the charging amount is insufficient to raise the energy level by one level. The probability of energy level conversion is expressed by the formula:

[0036] ; ; In the formula, This indicates that the energy level of the energy storage device in the wireless sensor at the beginning of a time slot is... It remains at the end of the time slot. The probability, Indicates intersection, This represents the minimum transmission power consumption required for the discretized wireless sensor to achieve the minimum transmission rate. Indicates the minimum transmission rate. This represents the lowest signal-to-noise ratio achieved by the gateway device signal to achieve the minimum transmission rate. This represents the noise power of Gaussian white noise in the environment; A5 ,in This indicates that at the beginning of a time slot, the remaining energy is insufficient to transmit data, and the energy level is raised to [a higher level]. The probability of energy level transition is expressed by the formula:

[0037]

[0038] ; In the formula, This indicates that the energy level of the energy storage device in the wireless sensor changes from a certain value within a time slot. Switch to The probability of; A6 ,in This indicates that the energy storage device in the wireless sensor has insufficient remaining energy to transmit data at the beginning of a time slot, and the energy level is raised to [value missing]. The probability of energy level transition is expressed by the formula:

[0039]

[0040] ; In the formula, This indicates that the energy level of the energy storage device in the wireless sensor changes from a certain value within a time slot. Switch to The probability of; A7 This indicates that the energy level of the energy storage device in the wireless sensor remains constant. Unchanged; that is, at the beginning of a time slot, the current data transmission channel quality is too poor, so even if all energy is exhausted, the transmission rate cannot be guaranteed. Therefore, energy is replenished, but because the energy storage device is already fully charged, the energy level remains unchanged; the probability of energy level transition is expressed by the formula: ; In the formula, This indicates that the energy level of the energy storage device in the wireless sensor remains unchanged. The probability remains unchanged; A8 ,in This indicates that at the start of the time slot, the remaining energy of the energy storage device is greater than the energy required to transmit data. Therefore, at the start of the time slot, the wireless sensor is in data transmission mode, and its energy decreases. At this time, the energy required to transmit data is... The probability of energy level transition is expressed by the formula:

[0041]

[0042] ; In the formula, This indicates that the energy level of the energy storage device in the wireless sensor changes from a certain value within a time slot. Switch to The probability of; The energy level transition probabilities of the eight cases A1-A8 above are combined into a... The energy conversion matrix of order X is expressed by the formula: ; In the formula, Represents the energy conversion matrix; Based on the energy conversion matrix, calculate the position of the wireless sensor at the [missing information]. The steady-state probability at each energy level is expressed by the formula: ; ; ; ; In the formula, Indicates that the wireless sensor is in the first position. The steady-state probability at each energy level Represents the energy conversion matrix. Represents the transpose of a matrix. express A matrix of order all 1s, express An identity matrix of order 1. Represents the rows of a matrix. Represents the columns of a matrix; express A unit column vector of order 1.

[0043] Furthermore, the average throughput of the wireless sensor transmission scheduling system requires calculating the probability that transmission requirements cannot be met at each energy level. This means iterating through the probability of each energy level occurring, the probability of transmission requirements not being met at that level, and the probability of both occurring simultaneously. This is expressed by the formula:

[0044]

[0045]

[0046] ; In the formula, This represents the average data throughput of the wireless sensor transmission scheduling system. This represents the probability that the remaining energy in the energy storage device of a wireless sensor is sufficient to support the minimum transmission energy consumption required for the wireless sensor to meet the minimum transmission rate. Optimize preset scheduling rules based on system average throughput.

[0047] Example 2: This embodiment proposes a wireless sensor transmission scheduling system suitable for self-powered scenarios, including the following modules: Communication system initialization module: Based on the operating characteristics of the point-to-point wireless communication system, a point-to-point wireless communication model is constructed. The point-to-point wireless communication model performs data transmission and energy harvesting activities according to the preset single time slot action rules, and obtains the operating status characteristic parameters of the wireless sensor, including real-time energy value, transmission energy consumption and channel gain. The point-to-point wireless communication system consists of a gateway device and a wireless sensor. Discrete energy level model building module: Based on the operating state characteristic parameters and the energy storage capacity of the wireless sensor, a discrete energy level model is constructed. The discrete energy level model divides the energy storage state into several energy levels and establishes the correspondence between each energy level and the remaining energy. State scheduling module: At the beginning of each time slot, the remaining energy corresponding to the current energy level of the wireless sensor is obtained based on the discrete energy level model. The remaining energy is compared with the energy consumption threshold, and scheduling decisions are executed according to the comparison results and preset scheduling rules. Scheduling optimization module: Records the throughput of the current time slot after executing the scheduling decision, calculates the system average throughput based on the throughput of each time slot, and optimizes the preset scheduling rules based on the system average throughput.

[0048] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, A and B simultaneously, or B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0049] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of electronic hardware and software. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0050] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0051] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0052] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A wireless sensor transmission scheduling method suitable for self-powered scenarios, characterized in that, The method includes: A point-to-point wireless communication model is constructed based on the operating characteristics of the point-to-point wireless communication system. The point-to-point wireless communication model performs data transmission and energy harvesting activities according to the preset single time slot action rules, and obtains the operating status characteristic parameters of the wireless sensor, including real-time energy value, transmission energy consumption and channel gain. The point-to-point wireless communication system consists of a gateway device and a wireless sensor. Based on the operating state characteristic parameters and the energy storage capacity of the wireless sensor, a discrete energy level model is constructed. The discrete energy level model divides the energy storage state into several energy levels and establishes the correspondence between each energy level and the remaining energy. At the beginning of each time slot, the remaining energy corresponding to the current energy level of the wireless sensor is obtained based on the discrete energy level model. The remaining energy is compared with the energy consumption threshold, and a scheduling decision is executed according to the comparison result and the preset scheduling rules. Record the throughput of the current time slot after executing the scheduling decision, calculate the system average throughput based on the throughput of each time slot, and optimize the preset scheduling rules based on the system average throughput.

2. The wireless sensor transmission scheduling method suitable for self-powered scenarios according to claim 1, characterized in that, The single-slot action rule specifically refers to the wireless sensor performing one of the following actions in each time slot: energy harvesting or data transmission.

3. The wireless sensor transmission scheduling method suitable for self-powered scenarios according to claim 1, characterized in that, The real-time energy value in the operating status characteristic parameters is expressed by the formula: ； In the formula, This represents the energy value collected by the wireless sensor in each time slot. Indicates energy conversion efficiency. Indicates downlink power gain. This indicates the fixed transmit power of the gateway device.

4. The wireless sensor transmission scheduling method suitable for self-powered scenarios according to claim 1, characterized in that, The energy consumption threshold is the discretized minimum transmission energy consumption that satisfies the minimum transmission rate, expressed by the formula: ； ； In the formula, Indicates the minimum transmission rate. This indicates the minimum power consumption required for a wireless sensor to meet the minimum transmission rate. Indicates uplink power gain. This represents the noise power of Gaussian white noise in the environment. This represents the minimum transmission energy consumption that satisfies the minimum transmission rate after discretization. Indicates that the wireless sensor is in the first position. The remaining energy at each energy level This means finding the condition in all energy levels. The smallest energy level that can be established , This indicates that the wireless sensor is in the first position. The remaining energy at each energy level.

5. A wireless sensor transmission scheduling method suitable for self-powered scenarios according to claim 1, characterized in that, The discrete energy level model is expressed by the following formula: ； In the formula, For energy level indexing, Indicates that the wireless sensor is in the first position. The remaining energy at each energy level Indicates the energy storage capacity of the wireless sensor. This indicates the number of discrete energy levels.

6. A wireless sensor transmission scheduling method suitable for self-powered scenarios according to claim 4, characterized in that, The preset scheduling rule is expressed as a formula: ； In the formula, Indicates the wireless sensor in the time slot real-time scheduling decisions Indicates energy harvesting operation. Indicates a data transfer operation. Indicates in time slot The remaining energy in the energy storage device of the wireless sensor.

7. A wireless sensor transmission scheduling method suitable for self-powered scenarios according to claim 4, characterized in that, Record the throughput of the current time slot after the scheduling decision is executed, and calculate the system average throughput based on the throughput of each time slot, expressed by the formula: ； In the formula, This represents the average data throughput of the wireless sensor transmission scheduling system. Indicates the minimum transmission rate. Represents probability. This represents the minimum transmission energy consumption that satisfies the minimum transmission rate after discretization. This indicates the remaining energy in the energy storage device of the wireless sensor. To express summation, Indicates the number of discrete energy levels. Indicates the energy storage capacity of the wireless sensor. Indicates that the wireless sensor is in the first position. The steady-state probability at each energy level This represents the minimum signal-to-noise ratio achieved by the gateway device signal to achieve the minimum transmission rate. This represents the noise power of Gaussian white noise in the environment. Indicates taking Exponentiation, Indicates the total downlink wireless power transfer channel gain. The average value, Represents the variable to be summed. Indicates the number of antennas. It represents factorial.

8. A wireless sensor transmission scheduling method suitable for self-powered scenarios according to claim 7, characterized in that, The steady-state probability is expressed by the formula: ； in: ； ； ； In the formula, Indicates that the wireless sensor is in the first position. The steady-state probability at each energy level Represents the energy conversion matrix. To represent the transpose of a matrix, express A matrix of order all 1s, express An identity matrix of order 1. Represents the rows of a matrix. Represents the columns of a matrix; express A unit column vector of order 1.

9. A wireless sensor transmission scheduling method suitable for self-powered scenarios according to claim 8, characterized in that, The energy conversion matrix is ​​expressed by the formula: ； In the formula, Represents the energy conversion matrix. This represents the probability that the energy level of the energy storage device in a wireless sensor is initially 0, and remains 0 after one time slot. This indicates that the energy level of the energy storage device in the wireless sensor changes from 0 to 1 within a time slot. The probability, This indicates that the energy level of the energy storage device in the wireless sensor changes from 0 to a certain value within one time slot. The probability, This indicates that the energy level of the energy storage device in the wireless sensor at the beginning of a time slot is... The time slot is still at the end of the time slot. The probability, This indicates that the energy level of the energy storage device in the wireless sensor changes from a certain value within a time slot. Switch to The probability, This indicates that the energy level of the energy storage device in the wireless sensor changes from a certain value within a time slot. Switch to The probability, This indicates that the energy level of the energy storage device in the wireless sensor remains unchanged. The probability remains constant; This indicates that the energy level of the energy storage device in the wireless sensor changes from a certain value within a time slot. Switch to The probability of.

10. A wireless sensor transmission scheduling system suitable for self-powered scenarios, characterized in that, Includes the following modules: Communication system initialization module: Based on the operating characteristics of the point-to-point wireless communication system, a point-to-point wireless communication model is constructed. The point-to-point wireless communication model performs data transmission and energy harvesting activities according to the preset single time slot action rules, and obtains the operating status characteristic parameters of the wireless sensor, including real-time energy value, transmission energy consumption and channel gain. The point-to-point wireless communication system consists of a gateway device and a wireless sensor. Discrete energy level model building module: Based on the operating state characteristic parameters and the energy storage capacity of the wireless sensor, a discrete energy level model is constructed. The discrete energy level model divides the energy storage state into several energy levels and establishes the correspondence between each energy level and the remaining energy. State scheduling module: At the beginning of each time slot, the remaining energy corresponding to the current energy level of the wireless sensor is obtained based on the discrete energy level model. The remaining energy is compared with the energy consumption threshold, and scheduling decisions are executed according to the comparison results and preset scheduling rules. Scheduling optimization module: Records the throughput of the current time slot after executing the scheduling decision, calculates the system average throughput based on the throughput of each time slot, and optimizes the preset scheduling rules based on the system average throughput.

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