A LoRa network adaptive data rate control method and system

Abstract

The present invention belongs to the field of LPWAN Internet of Things and discloses a LoRa network adaptive data rate control method and system. The present invention optimizes transmission power and data rate to reduce unnecessary energy consumption and extend the service life of terminal devices, especially for battery-powered devices. By dynamically adjusting the data rate, the present invention allows terminals to maintain communication even in weak signal conditions, improving overall network coverage and signal quality. The present invention optimizes communication parameters in the link state, helping to increase the packet reception rate, ensuring data transmission reliability and link stability. The present invention can adaptively adjust the number of terminals using different data rates in the network, increasing network throughput, improving transmission efficiency, and maintaining good communication quality.

Description

Technical Field

[0001] The present invention belongs to the technical field of LPWAN Internet of Things, and specifically relates to a LoRa network adaptive data rate control method and system. Background Art

[0002] LoRa (Long Range) is a communication method proposed by Semtech that uses linear frequency modulation spread spectrum technology. Among numerous Low Power Wide Area Network (LPWAN) technologies, LoRa offers unique advantages, including low power consumption, long transmission distance, strong anti-interference capabilities, and high network capacity. LoRaWAN, an LPWAN built using LoRa technology, is widely applicable to various IoT scenarios requiring long-distance communication. Since many IoT devices are deployed in environments where manual maintenance is difficult and are often battery-powered, IoT devices typically need to operate for extended periods of time in a low-power state to maximize battery life.

[0003] The physical layer of LoRa technology utilizes unique modulation and coding techniques, allowing devices using LoRa communication to select the appropriate data rate based on their deployment scenario. Selecting the data rate for a LoRa device simply requires setting the spreading factor and bandwidth. Wireless signals with different spreading factors interact orthogonally and do not interfere with each other. A gateway in a LoRa network can simultaneously demodulate multiple LoRa signals with different spreading factors and bandwidths.

[0004] Currently, research on adaptive data rate control methods in LoRa networks focuses on link-level optimization and low power consumption at the terminal level. Specifically, this aims to minimize terminal power consumption while ensuring communication quality between the terminal and the gateway. However, in scenarios with a large number of LoRa terminals, network performance must be considered, and existing methods struggle to meet application requirements. Furthermore, when LoRa terminals transmit data packets using the same spreading factor and bandwidth, collisions may occur, reducing network performance and increasing terminal power consumption. Therefore, an adaptive data rate control method combining link-level and network-level optimizations has been proposed. This method not only reduces power consumption by optimizing transmit power and data rate, but also improves overall network performance and further reduces terminal power consumption by adaptively adjusting the data rate of terminals in the network. This method is particularly suitable for IoT applications with a large number of terminals and limited power consumption.

[0005] In the prior art, the invention patent application "An Adaptive Rate Adjustment Method for LPWAN Internet of Things Based on Network Conditions" (Application No. 201711395954.7) proposes a method for adaptive rate adjustment based on network conditions. This method uses statistical data on the signal-to-noise ratio, signal strength, and frame sequence number of received uplink frames, combined with the spreading factor and channel load, to calculate the terminal's desired data rate and adjust it accordingly. However, this method primarily focuses on optimizing the communication link between the terminal and the gateway, lacking adaptability to complex application scenarios. For example, in a dense network with a large number of terminals, relying solely on link-level optimization may not effectively address packet collisions and network congestion caused by increased terminal density. Furthermore, this method does not fully consider the balance between terminal power consumption and overall network performance, making it difficult to meet power consumption constraints in certain application scenarios. Therefore, existing methods have certain limitations in practical deployment and cannot meet the needs of diverse IoT application scenarios.

[0006] The invention patent application "A dynamic transmission control method and system for a floating LoRa network" (application number 202111248808.8) proposes a method for dynamically controlling LoRa network transmission. This method determines the transmission power and data rate of different frequency bands by calculating the minimum signal-to-noise ratio, and optimizes the throughput by combining different spreading factors and polarization angles to correspond to data packet delivery rate and data rate. However, this method mainly relies on specific signal-to-noise ratios and regional parameters, and fails to comprehensively consider the optimization of network performance from a global perspective. In addition, the solution does not optimize the terminal transmit power, which may be limited in application scenarios where terminal power consumption is limited.

[0007] The invention patent application "A data transmission rate adaptive method based on the LoRaWAN network protocol" (application number 202110382337.3) proposes an adaptive data transmission rate adjustment method based on the LoRaWAN network protocol. This method utilizes the multiple spreading factors (SF) and multiple data rates of LoRa technology to dynamically adjust the data transmission rate according to the current channel conditions and signal-to-noise ratio (SNR) of the receiving end, thereby reducing the packet loss rate during data transmission and improving the system transmission performance. However, when optimizing the terminal communication link, this method only adjusts the data rate based on the signal-to-noise ratio, and fails to fully consider the reliability and stability of the communication link. In addition, this solution ignores the impact of data packet collisions on network performance when a large number of terminals exist simultaneously in the LoRa network, so it has limitations in scenarios with a large number of terminals.

[0008] The invention patent application "A LoRaWAN Network Rate Adaptive Adjustment Method Based on Channel State Identification" proposes a rate adaptive adjustment method based on channel state identification. This method establishes an estimation model for path-characterized packet loss probability and a data collision packet loss probability model, combined with channel state classification and identification, to adjust the rates of terminal devices in the network, aiming to improve the reliability and efficiency of data transmission. Although this method can effectively reduce packet loss and data collisions, and improve data packet throughput and transmission performance, establishing accurate packet loss and data collision probability models in actual applications may require a large amount of measurement data and computing resources. Furthermore, the implementation complexity of channel state classification and real-time rate adjustment is relatively high, with strict hardware and software requirements, which may limit its application in resource-constrained devices.

[0009] In summary, the adaptive data rate control method is necessary for the LoRa network to reduce terminal power consumption and improve network performance. Summary of the Invention

[0010] The purpose of the present invention is to overcome the above-mentioned shortcomings and provide a LoRa network adaptive data rate control method and system, which can ensure reliable communication between terminals and gateways, reduce the average power consumption of terminals, and improve network performance.

[0011] In order to achieve the above object, the present invention adopts the following technical solutions:

[0012] In a first aspect, the present invention provides a LoRa network adaptive data rate control method, comprising the following steps:

[0013] Continuously receive data packets sent by LoRa network terminals and count the link information of received data packets;

[0014] Obtain the link information of the LoRa network terminal within a fixed time window, and evaluate the link status of the LoRa network terminal based on the link information;

[0015] According to the link status, obtain a list of optional transmit power and data rates for LoRa network terminals under the premise of reachable communication;

[0016] Obtain a list of transmit power and data rates available to all terminals in the LoRa network under the premise of reachable communication, and select the initial values ​​of transmit power and data rate from the optional list to calculate the initial network performance indicators;

[0017] Based on the initialized network performance indicators, the initial values ​​of the terminal's transmit power and data rate and the list of optional transmit power and data rates for all terminals are used under the condition of limited terminal power consumption to obtain the optimal data rate for each terminal in the network and evaluate the optimal performance of the LoRa network.

[0018] A further improvement of the present invention is that the specific method of continuously receiving data packets sent by the LoRa network terminal and counting the link information of the received data packets is as follows:

[0019] The LoRa network terminal sends data packets according to the preset transmission power and data rate;

[0020] The link information of each terminal is collected based on the terminal ID in the received data packet.

[0021] A further improvement of the present invention is that the received data packet information includes signal-to-noise ratio, signal strength and data information;

[0022] The link information of each terminal includes the signal-to-noise ratio (SNR) and signal strength (RSSI) of the data packet.

[0023] A further improvement of the present invention is that the specific method for obtaining the link information of the LoRa network terminal within a fixed time window and evaluating the link status of the LoRa network terminal according to the link information is as follows:

[0024] Continuously obtain link information of data packets within a fixed time window and calculate the statistical link information of the data packets sent by the terminal;

[0025] Use the combined weighting method to evaluate the link status of the terminal.

[0026] A further improvement of the present invention is that the specific method of using the combined weighting method to evaluate the link status of the terminal is as follows:

[0027] Normalize the statistical link information and use the fuzzy analytic hierarchy process to calculate the subjective weight of the statistical link information;

[0028] The objective weight of statistical link information is calculated using the CRITIC method, and the objective weight is optimized using the VIKOR method;

[0029] The subjective weight is combined with the optimized objective weight using the multiplication synthesis method to obtain the combined weight. The combined weight and the normalized corresponding statistical link information are used to obtain the terminal link status score.

[0030] A further improvement of the present invention is that, based on the link status, a specific method for calculating a list of optional transmit powers and data rates of a LoRa network terminal under the premise of reachable communication is as follows:

[0031] According to the link status of the LoRa network terminal, calculate the signal-to-noise ratio margin and link budget margin of the LoRa network terminal;

[0032] According to the link information of the LoRa network terminal, the signal-to-noise ratio margin and the link budget margin are combined to obtain the signal-to-noise ratio margin and the theoretical link budget;

[0033] Based on the signal-to-noise ratio margin and theoretical link budget, calculate the list of optional transmit power and data rates for LoRa network terminals under the premise of reachable communication.

[0034] A further improvement of the present invention is that, based on the signal-to-noise ratio margin and the theoretical link budget, a specific method for calculating the list of optional transmit power and data rates of the LoRa network terminal under the premise of reachable communication is as follows:

[0035] Determine the adequacy of link resources based on the signal-to-noise ratio margin. When link resources are redundant, reduce the spreading factor to increase the data rate or reduce the transmit power to reduce power consumption. When link resources are insufficient, increase the transmit power to improve the received signal quality or increase the spreading factor to reduce the data rate.

[0036] When the theoretical link is higher than the preset value, the bandwidth is increased to increase the data rate; when the theoretical link is lower than the preset value, the bandwidth is reduced to reduce the data rate;

[0037] Based on the signal-to-noise ratio margin SNR Margin and the value of the theoretical link budget LM, a list of optional transmit powers and data rates is obtained under the premise that terminal communication is reachable.

[0038] A further improvement of the present invention is that, based on the initialization network performance index, the initial values ​​of the terminal's transmit power and data rate and the list of transmit power and data rates optional for all terminals are used under the condition of limited terminal power consumption to obtain the optimal data rate for each terminal in the network and evaluate the optimal performance of the LoRa network. The specific method is as follows:

[0039] Based on transmit power and data rate, a network performance optimization model is established and the objective function is determined under the condition of limited terminal power consumption;

[0040] Based on the initial values ​​of transmit power and data rate, combined with the power consumption limit of the LoRa network terminal, the optimal data rate for each terminal is obtained;

[0041] Based on the adaptive optimal data rate of each terminal, the network performance indicators are calculated to evaluate the optimal performance of the LoRa network.

[0042] A further improvement of the present invention is that, based on a list of transmit power and data rates selectable by all terminals, a specific method for establishing a network performance optimization model and determining an objective function under the condition of limited terminal power consumption is as follows:

[0043] Initialize the network performance indicators of network throughput Γ and terminal average power consumption E Avg and the average terminal delay T AvgPerform normalization processing and use the FAHP method to calculate the subjective weight of statistical link information;

[0044] The objective weights were calculated using the improved CRITIC method and optimized using the VIKOR method;

[0045] The subjective weights are combined with the optimized objective weights using the multiplication synthesis method to obtain the combined weights. The combined weights and the normalized network performance indicators are used to obtain the network performance score S. The calculation process of this performance score is the objective function of the optimization problem.

[0046] Based on the initial values ​​of transmit power and data rate, combined with the power consumption limit of the LoRa network terminal, the specific method for obtaining the optimal data rate for each terminal is as follows:

[0047] The initial values ​​of the transmit power and data rate of all terminals in the LoRa network are used as the initial solution to the optimization problem. The Zebra optimization algorithm is used to solve the optimization problem. Starting from the initial solution, the algorithm randomly searches the list of optional transmit power and data rate for all terminals in the LoRa network, and obtains the adaptive data rate that optimizes the performance of the LoRa network under the condition of limited terminal power consumption.

[0048] The specific method for calculating network performance indicators and evaluating the optimal performance of the LoRa network based on the adaptive optimal data rate of each terminal is as follows:

[0049] The optimal data rate of each terminal in the LoRa network is adaptive, and the transmission power of each terminal in the LoRa network is combined to calculate the network performance indicators of network throughput Γ and terminal average power consumption E. Avg and the average terminal delay T Avg , the combined weighted method is used to obtain the network performance score and complete the optimal performance evaluation of the LoRa network under the condition of limited terminal power consumption.

[0050] In a second aspect, the present invention provides a LoRa network adaptive data rate control system, comprising:

[0051] The link information acquisition module is used to continuously receive data packets sent by the LoRa network terminal and count the link information of the received data packets;

[0052] The link status acquisition module is used to obtain the link information of the LoRa network terminal within a fixed time window and evaluate the link status of the LoRa network terminal based on the link information;

[0053] The rate list acquisition module is used to obtain the optional transmission power and data rate list of the LoRa network terminal under the premise of communication reachability based on the link status;

[0054] The performance index acquisition module is used to obtain a list of optional transmit power and data rate for all terminals in the LoRa network under the premise of reachable communication, and select the initial values ​​of transmit power and data rate from the optional list to calculate the initial network performance index;

[0055] Based on the link status of the terminal and the initialized network performance indicators, the initial values ​​of the terminal's transmit power and data rate and the list of optional transmit power and data rates for all terminals are used under the condition of limited terminal power consumption to obtain the optimal data rate for each terminal in the network and evaluate the optimal performance of the LoRa network.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] The present invention reduces unnecessary energy consumption and extends the service life of terminal devices by optimizing transmission power and data rate, especially for devices that rely on battery power. The present invention dynamically adjusts the data rate so that the terminal can still maintain communication when the signal is weak, thereby improving the overall network coverage and signal quality. The present invention optimizes the communication parameters under the link state, which helps to improve the data packet reception rate and ensure the reliability of data transmission and the stability of the link. The present invention can adaptively adjust the number of terminals using different data rates in the network, increase network throughput, improve transmission efficiency, and maintain good communication quality. The present invention can flexibly adjust communication parameters according to the location of the terminal and environmental changes, ensuring that a stable connection can be maintained in different application scenarios, and is suitable for various Internet of Things application scenarios. By reducing terminal power consumption and improving communication efficiency, the present invention can reduce the cost of equipment maintenance and network management and improve the economic efficiency of operations. In summary, the present invention not only technically improves the performance of the LoRa network, but also provides support for the sustainability and economy of Internet of Things applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 A flow chart of the LoRa network adaptive data rate control method of the present invention;

[0059] Figure 2 A system structure diagram of the LoRa network adaptive data rate control method of the present invention;

[0060] Figure 3 A flowchart of an algorithm for obtaining a list of optional transmit powers and data rates based on a link state under the premise that terminal communication is reachable according to the present invention;

[0061] Figure 4 1 is a block diagram of a LoRa network adaptive data rate control method of the present invention;

[0062] Figure 5Flowchart of the implementation of the LoRa network adaptive data rate control method of the present invention;

[0063] Figure 6 A comparison diagram of data packet reception rates of a single terminal at an adaptive data rate and a fixed data rate according to the present invention;

[0064] Figure 7 This is a comparison chart of the average power consumption of terminals with the adaptive data rate solution of the present invention and other data rate solutions;

[0065] Figure 8 This is a comparison chart of the network throughput and average terminal delay of the adaptive data rate solution of the present invention and other data rate solutions. DETAILED DESCRIPTION

[0066] In order to further understand the content of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the embodiments are only for explaining the present invention and are not intended to limit it.

[0067] See also Figure 1 , a LoRa network adaptive data rate control method, comprising the following steps:

[0068] S1, continuously receives data packets sent by the LoRa network terminal and counts the link information of the received data packets.

[0069] S2, obtains the link information of the LoRa network terminal within a fixed time window, and evaluates the link status of the LoRa network terminal based on the link information.

[0070] S3, based on the link status, obtains a list of optional transmit powers and data rates for LoRa network terminals under the premise of reachable communication.

[0071] S4, according to the list of optional transmission power and data rate corresponding to all terminals under the premise of reachable communication in the LoRa network, select the initial values ​​of transmission power and data rate from the optional list to calculate the initialization network performance index.

[0072] S5, based on the initialized network performance indicators, uses the initial values ​​of the terminal's transmit power and data rate and the list of optional transmit power and data rates for all terminals under the condition of limited terminal power consumption to obtain the optimal data rate adapted by each terminal in the network and evaluate the optimal performance of the LoRa network.

[0073] See also Figure 2 , a LoRa network adaptive data rate control system, comprising:

[0074] The link information acquisition module is used to continuously receive data packets sent by the LoRa network terminal and count the link information of the received data packets;

[0075] The link status acquisition module is used to obtain the link information of the LoRa network terminal within a fixed time window and evaluate the link status of the LoRa network terminal based on the link information;

[0076] The rate list acquisition module is used to obtain the optional transmission power and data rate list of the LoRa network terminal under the premise of communication reachability based on the link status;

[0077] The performance index acquisition module is used to obtain a list of optional transmit power and data rate for all terminals in the LoRa network under the premise of reachable communication, and select the initial values ​​of transmit power and data rate from the optional list to calculate the initial network performance index;

[0078] Based on the link status of the terminal and the initialized network performance indicators, the initial values ​​of the terminal's transmit power and data rate and the list of optional transmit power and data rates for all terminals are used under the condition of limited terminal power consumption to obtain the optimal data rate for each terminal in the network and evaluate the optimal performance of the LoRa network.

[0079] Example 1:

[0080] This embodiment further limits the step S1, and the specific method of continuously receiving data packets sent by the LoRa network terminal and counting the link information of the received data packets is as follows:

[0081] S11, the terminal in the LoRa network sends a data packet to the gateway according to the preset transmission power and data rate; wherein, the data rate and transmission power selected by the terminal should ensure that it can communicate with the gateway, for example, using the maximum transmission power and the minimum data rate.

[0082] S12: The gateway forwards the successfully received data packets to the network server, which counts the link information of each terminal based on the terminal ID. The data packets successfully received by the gateway should include the signal-to-noise ratio, signal strength, and data information. The network server counts the signal-to-noise ratio (SNR) and signal strength (RSSI) of multiple data packets sent by the terminal based on the terminal ID.

[0083] Example 2:

[0084] This embodiment further limits the step S2, and the specific method of obtaining the link information of the LoRa network terminal within a fixed time window and evaluating the link status of the LoRa network terminal based on the link information is as follows:

[0085] S21, continuously obtain the link information of the data packet within the fixed time window, and the network server calculates the statistical link information of the terminal sending the data packet. Among them, the average signal-to-noise ratio SNR is calculated within the fixed time windowAvg , average signal strength RSSI Avg , packet reception rate PRR, signal-to-noise ratio coefficient of variation CV SNR and signal intensity variation coefficient CV RSSI .

[0086] S22, using a combined weighting method to evaluate the terminal's link status, wherein the statistical link information is normalized, the subjective weight of the statistical link information is calculated using the FAHP method, the objective weight is calculated using the CRITIC method, and the objective weight is optimized using the VIKOR method. The subjective weight is combined with the optimized objective weight using a multiplication synthesis method to obtain a combined weight, and the combined weight is combined with the normalized corresponding statistical link information to obtain a terminal link status score.

[0087] Example 3:

[0088] This embodiment further limits the step S3. The specific method for obtaining a list of optional transmit powers and data rates of LoRa network terminals under the premise of reachable communication according to the link status is as follows:

[0089] S31, according to the link status of the LoRa network terminal, calculate the signal-to-noise ratio margin and link budget margin of the LoRa network terminal; wherein, the higher the link status score, the more stable and reliable the link, and the smaller the values ​​of the signal-to-noise ratio margin M1 and the link budget margin M2 should be; the lower the link status score, the poorer the link stability, and the larger the values ​​of the signal-to-noise ratio margin M1 and the link budget margin M2 should be.

[0090] S32, according to the link information of the LoRa network terminal, combined with the signal-to-noise ratio margin and the link budget margin, obtains the signal-to-noise ratio margin and the theoretical link budget; wherein, the signal-to-noise ratio margin SNR Margin Using the average signal-to-noise ratio SNR Avg , signal-to-noise ratio margin M1, the minimum demodulation signal-to-noise ratio required by the spreading factor used by the terminal; the theoretical link budget LM uses the average signal strength RSSI Avg , the link budget margin M2 obtained by S22, and the receiver sensitivity under the current communication parameters of the terminal are calculated.

[0091] S33, based on the signal-to-noise ratio margin and the theoretical link budget, calculate the list of optional transmission power and data rates for the LoRa network terminal under the premise of reachable communication. Among them, the abundance of link resources is determined based on the obtained signal-to-noise ratio margin. When the link resources are redundant, reduce the spreading factor to increase the data rate or reduce the transmission power to reduce power consumption. When the link resources are insufficient, increase the transmission power to improve the quality of the received signal or increase the spreading factor to reduce the data rate. In addition, when the theoretical link budget is large, increase the bandwidth to increase the data rate; when the theoretical link budget is small, reduce the bandwidth to reduce the data rate. Based on the signal-to-noise ratio margin SNR Margin and the value of the theoretical link budget LM, and outputs a list of optional transmit powers and data rates under the premise that terminal communication is reachable according to the set algorithm steps.

[0092] Example 4:

[0093] This embodiment further limits the step S4. Based on the initialization network performance indicator, a list of optional transmit power and data rates for all terminals in the LoRa network under the premise of reachable communication is obtained. The specific method for selecting the initial values ​​of transmit power and data rate from the optional list to calculate the initialization network performance indicator is as follows:

[0094] S41, obtaining a list of transmit powers and data rates that can be selected by all terminals under the premise of reachable communication in the network;

[0095] S42, select the maximum data rate in the optional data rate list of each terminal as the initial data rate value of the terminal; wherein, according to the data rate list, select the minimum spreading factor and maximum bandwidth combination of each terminal, that is, the maximum data rate under the premise of reachable communication as the initial data rate value of the terminal.

[0096] S43, using the transmission power and data rate initial values ​​obtained in S42 to calculate the network initialization performance index; wherein, according to the transmission power and data rate initial values ​​corresponding to each terminal, the network performance index is calculated, and the network performance index includes network throughput Γ, terminal average power consumption E Avg , terminal average delay T Avg .

[0097] Example 5:

[0098] This embodiment further limits the step of S5. Based on the initialization of network performance indicators, the initial values ​​of the terminal's transmit power and data rate and the list of transmit power and data rates optional for all terminals are used under the condition of limited terminal power consumption to obtain the optimal data rate adapted by each terminal in the network, and the specific method for evaluating the optimal performance of the LoRa network is as follows:

[0099] S51, based on the calculation method of network performance indicators and the network performance evaluation method, combined with the list of optional transmission power and data rate of all terminals, establish a network performance optimization model and determine the objective function under the condition of limited terminal power consumption; wherein, first, the network throughput Γ obtained in D3) and the average terminal power consumption E Avg and the average terminal delay T Avg Normalization is performed, and the subjective weights of the network performance indicators are calculated using the FAHP method. The objective weights are calculated using the improved CRITIC method, and the objective weights are optimized using the VIKOR method. The subjective weights are combined with the optimized objective weights using the multiplication synthesis method to obtain a combined weight. The combined weights and the normalized network performance indicators are used to obtain the network performance score S. The calculation process of this performance score is the objective function of the optimization problem. Under the premise of limited terminal power consumption, this objective function maximizes network throughput and minimizes average terminal latency. The alternative solution to the optimization problem is the list of optional transmission powers and data rates for all terminals obtained in step D) under the premise of reachable communication.

[0100] S52: Based on the corresponding transmit power and initial data rate values ​​of the terminal, and taking into account the power consumption constraints of the terminal, an optimization algorithm is used to obtain the optimal adaptive data rate for each terminal. The initial transmit power and data rate values ​​of all terminals in the network are used as the initial solution to the optimization problem, and the Zebra Optimization Algorithm (ZOA) is used to solve the optimization problem. Within a set number of iterations, the ZOA randomly searches for the optimal solution at different stages by simulating the distribution and movement strategies of zebras in a group. Starting from the initial solution, the algorithm randomly searches the list of available transmit power and data rates for all terminals in the LoRa network, seeking the adaptive data rate that optimizes network performance under the condition of limited terminal power consumption.

[0101] S53, based on the optimal data rate adapted by each terminal, calculate the network performance index, and use the algorithm to evaluate the optimal performance of the LoRa network. Among them, based on the optimal data rate adapted by each terminal in the network in step S52, combined with the transmission power of each terminal in the network, calculate the network performance index network throughput Γ, terminal average power consumption E Avg and the average terminal delay T Avg , the combined weighted method is used to obtain the network performance score and complete the optimal performance evaluation of the LoRa network under the condition of limited terminal power consumption.

[0102] Example 6:

[0103] A method for controlling a LoRa network's adaptive data rate comprises the following steps:

[0104] S1: A single terminal sends data packets at a fixed data rate, and the network server collects statistics on the link information of the received data packets.

[0105] The terminals in the LoRa network send data packets to the gateway according to the preset transmission power and data rate. The transmission power and data rate selected by the terminal should ensure communication with the gateway, such as using the maximum transmission power and the minimum data rate. The gateway forwards the successfully received data packets to the network server. The network server counts the link information of the terminal according to the terminal ID. The data packets successfully received by the gateway should contain signal-to-noise ratio, signal strength, and data information. The network server counts the signal-to-noise ratio (SNR) and signal strength (RSSI) of multiple data packets sent by the terminal according to the terminal ID.

[0106] S2: Repeat S1 within a fixed time window to calculate the statistical link information of the terminal and use the algorithm to evaluate the link status of the terminal.

[0107] The terminal's statistical link information includes the average signal-to-noise ratio (SNR) Avg , average signal strength RSSI Avg , packet reception rate PRR, signal-to-noise ratio coefficient of variation CV SNR and signal intensity variation coefficient CV RSSI A total of n data packets are received in the window, and the signal-to-noise ratio and signal strength when the jth data packet is received are: SNR j and RSSI j , the calculation formula for statistical reception information is:

[0108]

[0109] The obtained statistical link information is normalized and the subjective weight of the statistical link information is calculated using the FAHP method. The objective weight is calculated using the CRITIC method, and the objective weight is optimized using the VIKOR method. The subjective weight is combined with the optimized objective weight using the multiplication synthesis method to obtain a combined weight. The combined weight and the normalized corresponding statistical link information are used to obtain the terminal link status score. The terminal link status score is calculated as follows:

[0110]

[0111] in, is the normalized value of the statistical link information, (ω1,ω2,ω3,ω4,ω5) represents the combined weight corresponding to each statistical link information, and the link status score Score ranges from [0 to 1]. The signal-to-noise ratio margin and link budget are calculated based on the calculated link status scores and statistical link information.

[0112] S3: Based on the link status obtained in S2 and combined with the terminal's statistical link information, an algorithm is used to output a list of optional transmit powers and data rates for the terminal under the premise of reachable communication.

[0113] The average signal-to-noise ratio and average signal strength of the terminal are SNR Avg and RSSI Avg , calculate the signal-to-noise ratio margin SNR of the current link of the terminal Margin And the theoretical link budget LM, calculated as:

[0114] SNR Margin =SNR Avg -SNR Min -M1

[0115] LM=RSSI Avg -Sensitivity-M2

[0116] Where, SNR Avg and RSSI Avg Respectively represent the average signal-to-noise ratio and average signal strength of the data packets received in the window; SNR Min Indicates the minimum demodulation signal-to-noise ratio corresponding to the spreading factor used by the current terminal; Sensitivity indicates the receiver sensitivity under the current communication parameters of the terminal. The calculation formula for receiver sensitivity is as follows:

[0117] Sensitivity=-174+NF+10lgBW+SNR Min (dBm)

[0118] Where NF represents the noise figure of the LoRa receiver; BW is the modulation bandwidth of the LoRa signal; the spreading factor used by the terminal is related to the minimum demodulation signal-to-noise ratio SNR. Min The corresponding relationship is shown in Table 1:

[0119] Table 1 Correspondence between spreading factor and minimum demodulation signal-to-noise ratio

[0120]

[0121] M1 and M2 are the signal-to-noise ratio margin and link budget margin obtained based on the current link status. When the terminal's link status score is Score, M1∈[0,10]dB, M2∈[10,30]dB, M1 and M2 can be calculated as:

[0122] M1=10(1-Score)

[0123] M2=30-20·Score

[0124] Figure 3 The algorithm flow chart of the present invention is to obtain the list of optional transmission power and data rate under the premise of terminal communication reachability based on the link status, according to the obtained signal-to-noise ratio margin SNR Margin , when NStep When >0, it means that the link resources are redundant, and priority is given to reducing the spreading factor to increase the data rate; when the spreading factor is the minimum SF=7, reduce the transmit power to reduce power consumption; each time the parameter is adjusted, N Step -1. When N Step <0, indicating insufficient link resources, give priority to increasing the transmit power to improve the quality of the received signal; when the maximum transmit power TP = 20dB, increase the spreading factor and reduce the data rate; each time the parameter is adjusted, N Step +1. When N Step = 0, transmit power and spreading factor adjustment ends. Furthermore, when LM - 3dB > 0 and the bandwidth (BW) is not at its maximum, that is, BW < 500kHz, the link budget is sufficient, the bandwidth is doubled, and the data rate is increased. Each bandwidth adjustment increments LM - 3dB. When LM + 3dB < 0 and the bandwidth (BW) is not at its minimum, that is, BW > 62.5kHz, the link budget is insufficient, the bandwidth is halved, and the data rate is reduced. Each bandwidth adjustment increments LM + 3dB. Bandwidth adjustment ends when LM = 0 or the bandwidth reaches its maximum value. Following the algorithm steps, a list of selectable transmit power and data rates is output, assuming reachable terminal communication.

[0125] S4: Repeat steps S1 to S3 to obtain a list of optional transmit power and data rates under the premise that all terminals in the LoRa network can communicate, and use the algorithm to select the initial values ​​of transmit power and data rate from the list to calculate the initial network performance index.

[0126] The maximum data rate in each terminal's optional data rate list is selected as the initial value of the terminal data rate. Combined with the terminal's transmit power list, the network performance indicators are calculated. The indicators include network throughput LM=0, terminal average power consumption E Avg , terminal average delay T Avg .

[0127] The calculation formula of network throughput Γ is as follows:

[0128]

[0129] Among them, λ represents the number of data packets sent by the terminal per unit time; L represents the length of a single data packet; R b_i Indicates the actual data rate of the terminal, which is calculated as follows:

[0130]

[0131] Where SF represents the spreading factor used by the terminal to send data packets; BW represents the modulation bandwidth of the terminal to send data packets; CR represents the coding rate, which ranges from 1 to 4. i Indicates the use of R b_iThe total traffic generated by all terminals of the transmission is calculated as follows:

[0132]

[0133] Where N i Indicates the use of R b_i The number of terminals transmitted; T Interval Indicates the average time interval between data packets generated by each terminal node.

[0134] Average terminal power consumption E Avg The calculation formula is as follows:

[0135]

[0136] Among them, n represents the total number of terminals in the LoRa network; m represents the number of different transmission power and data rate combinations used by the terminals in the network; n i Indicates the data rate R used b_i The number of terminals. avg_i Indicates the data rate R used b_i The average energy consumption of a terminal that successfully transmits a data packet is avg_i The calculation formula is as follows:

[0137]

[0138] Where, E total_ik Indicates the data rate R used by the terminal b_i and transmit power TP i Power consumption when transmitting the kth data packet; N i Indicates the number of data packets transmitted successfully. Furthermore, the terminal uses a data rate R b_i and transmit power TP i The power consumption E of successfully transmitting a frame of data total The calculation formula is as follows:

[0139]

[0140] Among them, the active power consumption is E work , sleep power consumption is E sleep , the terminal sleep power consumption is small and can be ignored. Consider the results of the terminal transmitting data frames under the ALOHA model: the transmission fails and needs to be retransmitted, and the transmission is successful. Assuming that the probability of successful transmission without collision is p, the active power consumption E work Power consumption E caused by transmission failure due to collision fail And the power consumption E of successful transmission success Among them, E success Wake-up power consumption E awake , sampling power consumption E sample, Transmitting power consumption E TX , idle power consumption E idle and receiving power consumption E RX Composition; E fail E success Idle power consumption E idle and receiving power consumption E RX The power consumption is doubled. Furthermore, E awake 、E sample 、E idle and E RX The calculation of E should be determined based on the actual terminal hardware composition and the specific service duration. TX The size of is related to the transmit power and data rate used by the terminal, and its calculation formula is as follows:

[0141] E TX =U·I(TP)·ToA(BW,SF,CR,L)

[0142] Among them, U represents the operating voltage of the terminal; I(TP) represents the operating current when the terminal uses the current transmission power TP; ToA represents the data rate R used by the terminal b_i (BW, SF, CR) is the air transmission time of a data packet with a packet length of L. The calculation formula of ToA is as follows:

[0143]

[0144] Among them, R s Indicates the symbol rate, N symbol Indicates the number of symbols in a data packet. Among them, the symbol rate R s The calculation formula is as follows:

[0145]

[0146] Where BW represents the modulation bandwidth and SF represents the spreading factor. symbol The calculation formula is as follows:

[0147]

[0148] Among them, L preamble Indicates the preamble length; L indicates the number of bytes of the message to be sent; L can be 0 or 1, indicating whether the physical layer header exists; ceil(·) indicates rounding up; BW indicates the modulation bandwidth; SF indicates the spreading factor; CR indicates the coding rate, which ranges from 1 to 4.

[0149] Terminal average delay T Avg The calculation formula is as follows:

[0150]

[0151] Where n represents the number of terminals in the network; m represents the number of terminals in the network using different data rates; n i Indicates the data rate R used b_i The average terminal delay T of the entire LoRa network is calculated using the weighted scoring method. avg . Further, using the data rate R b_i Average terminal delay T for sending data packets avg_i The calculation formula is as follows:

[0152]

[0153] Among them, P success represents the probability of successful transmission; T fail Indicates the delay of transmission failure caused by collision; T success Indicates the delay of successful transmission. For LoRa terminals that transmit data packets under the ALOHA protocol, the data rate R b_i The transmission success probability P of the sent data packet success The calculation formula is as follows:

[0154]

[0155] Among them, λ i Indicates the use of R b_i The total traffic generated by all terminals during transmission; λ represents the number of data packets sent by the terminal per unit time; L represents the length of a single data packet. Furthermore, the delay for successful transmission, T success The time required for the terminal to generate a data packet The air transmission time ToA required to send uplink data at a given data rate UL Composition. Transmission failure delay T fail It includes the time from when the terminal generates a data packet to when the terminal receives the ACK timeout, as well as the time from the next retransmission until the transmission is successful. Therefore, T fail and T success The calculation formula is as follows:

[0156]

[0157] Where, Indicates the time required for the terminal to generate a data packet, which is mainly related to the terminal hardware and spreading factor parameters; ToA UL Indicates the air transmission time required to send uplink data at a given data rate; T wait Indicates the time it takes for the terminal to open the receiving window after sending the data packet; T RX Indicates the duration of the terminal receiving window opening; T IntervalIndicates the time interval from the failure of the terminal to the next retransmission of the data packet. The calculation formula is as follows:

[0158]

[0159] Where x represents the average rate at which the terminal generates data packets.

[0160] S5: Based on the initialized network performance indicators in step S4, using the initial values ​​of the terminal's transmit power and data rate, and the list of optional transmit power and data rates for all terminals, an algorithm is designed to obtain the optimal data rate for each terminal in the network and evaluate the optimal performance of the LoRa network.

[0161] Assume that there are n terminals in the network, using m different data rates, and the gateway can simultaneously demodulate LoRa data packets with 8 different data rates. The optional transmission power of each terminal in the network is TP i , the optional spreading factor list is listSF i , the optional bandwidth list is listBW i , data rate DR k The corresponding number of terminals is num k The optimization goal of the optimization problem is the network performance score S(Γ,E avg ,T avg ) is maximized, the optimization problem can be expressed as follows

[0162] max S(Γ,E avg ,T avg )

[0163]

[0164] The calculation of the network performance score S requires normalizing the network performance indicators. The FAHP method is used to calculate the subjective weight of the statistical link information. The improved CRITIC method is used to calculate the objective weight, and the VIKOR method is used to optimize the objective weight. The subjective weight is combined with the optimized objective weight using the multiplication synthesis method to obtain the combined weight. The combined weight and the normalized network performance indicators are used to obtain the network performance score S. The calculation process of this performance score is the objective function of the optimization problem. The alternative solution to the optimization problem is: a list of optional transmission power and data rates under the premise that all terminals can communicate. Exemplarily, the method for calculating network performance is as follows:

[0165]

[0166] Among them, (c1, c2, c3) represents the weight corresponding to each network performance indicator, Represents the normalized values ​​of the three sexual indices.

[0167] The initial values ​​of the transmission power and data rate of each terminal in the network are used as the initial solution to the optimization problem, and the zebra optimization algorithm (ZOA) is used to solve the optimization problem. Within the set number of iterations, ZOA simulates the distribution and movement strategy of zebras in the group and randomly searches for the optimal solution in different stages. Starting from the initial solution, the algorithm randomly searches the list of optional transmission power and data rates for all terminals in the network to obtain the optimal data rate that each terminal can adapt to when the network performance is optimal. Based on the optimal data rate that each terminal adapts to in the network and combined with the transmission power of each terminal in the network, the network performance indicators network throughput Γ and terminal average power consumption E are calculated. Avg and the average terminal delay T Avg ,The optimal performance of the LoRa network is evaluated using the ,combined weighting method.

[0168] Figure 4 This is a block diagram of the LoRa network adaptive data rate control method with limited terminal power consumption of the present invention, which details the implementation process of the adaptive data rate control method of the present invention.

[0169] The system involved in the present invention includes at least a LoRa terminal, a gateway, a network server, and an application server. The statistics of the following terminal link information, the operation of the algorithm, and the calculation of related indicators are all completed by the network server.

[0170] like Figure 5 As shown, an embodiment of the present invention provides an implementation flow chart of a LoRa network adaptive data rate control method with limited terminal power consumption, which specifically includes the following steps S100 to S105.

[0171] Step S100: The terminal sends a data packet and the network server collects statistics on the terminal link information, which includes the signal-to-noise ratio and signal strength.

[0172] Step S101: The network server calculates terminal statistical link information within a fixed time window. The terminal statistical link information includes the average signal-to-noise ratio (SNR). Avg , average signal strength RSSI Avg , packet reception rate PRR, signal-to-noise ratio coefficient of variation CV SNR and signal intensity variation coefficient CV RSSI .

[0173] Step S102 : Evaluate the link status and calculate the signal-to-noise ratio margin and theoretical link budget.

[0174] Step S103: using an algorithm to obtain a list of transmit powers and data rates that can be selected by the terminal under the premise of reachable communication.

[0175] Step S104: Repeat steps S100 to S103, and select initial values ​​of transmit power and data rate from the list to calculate and initialize network performance indicators.

[0176] Step S105 , evaluating the performance of the initialized network, using an optimization algorithm to obtain the optimal transmission power and data rate of each terminal in the network and evaluating the optimal performance of the network.

[0177] According to steps S100 to S101, the network server counts the terminal link information and calculates the terminal statistical link information within a fixed time window. For example, assuming that the network server receives a total of n data packets sent by the terminal with terminal ID num within the window, the signal-to-noise ratio and signal strength when the jth data packet is received are: SNR j and RSSI j Based on the information obtained, calculate the statistical link information: average signal-to-noise ratio SNR Avg , average signal strength RSSI Avg , packet reception rate PRR, signal-to-noise ratio coefficient of variation CV SNR and signal intensity variation coefficient CV RSSI .

[0178] According to step S102, the link status is evaluated and the signal-to-noise ratio margin and the theoretical link budget are calculated. For example, a combined weighting method is used to evaluate the link status and a link status evaluation model is established:

[0179]

[0180] Where (ω1, ω2, ω3, ω4, ω5) represents the combined weight corresponding to each statistical link information, and the link status score (Score) ranges from [0 to 1]. The subjective weights of the statistical link information are calculated using the FAHP method; the objective weights are calculated using the CRITIC method, and the objective weights are optimized using the VIKOR method. The subjective weights are combined with the optimized objective weights using the multiplicative synthesis method to obtain the combined weights. The weighting results are shown in Table 2.

[0181] Table 2 Example of parameter weights

[0182]

[0183] For example, let the average signal strength RSSI of terminal i obtained within a fixed time window be Avg -63.25dB; packet reception rate PRR is 1; average signal-to-noise ratio SNR Avg The signal strength coefficient of variation is 7dB; the signal strength coefficient of variation is 0.060592; and the signal-to-noise ratio coefficient of variation is 0.534522. Calculate the link status score:

[0184]

[0185] Furthermore, the signal-to-noise ratio margin SNR can be calculated based on the link performance score. Margin And the theoretical link budget LM. Assume that the spreading factor used by the terminal i is 8 and the modulation bandwidth is 125kHz. Combined with the obtained link score Score and the average signal-to-noise ratio SNR Avg , average signal strength RSSI Avg , the signal-to-noise ratio margin SNR of the terminal Margin And the theoretical link budget LM is calculated as follows:

[0186] SNR Margin =SNR Avg -SNR Min -M1=7-(-10)-10(1-0.7288)=14.288dB

[0187] LM=RSSI Avg -Sensitivity-M2=-63.25-(-127)-[30-20×0.7288]=48.326dB

[0188] According to step S103, the algorithm is used to obtain a list of transmit power and data rates that the terminal can select under the premise of reachable communication. For example, assume that the spreading factor used by terminal i is 8, the modulation bandwidth is 500kHz, and the coding rate is 4 / 5, that is, the data rate is 3.13kbps and the transmit power is 20dBm. According to the signal-to-noise ratio margin SNR of the terminal Margin =14.288dB The number of iterations of the calculation algorithm N step , the calculation formula is as follows:

[0189]

[0190] according to Figure 3 The algorithm process of obtaining the list of terminal optional transmission power and data rate under the premise of communication reachability, N step =5>0 and SF=8>7, adjust the spreading factor to 7, N step =4; TP = 20dB>3dB, adjust the transmission power four times, reducing it by 3dB each time. step =0, TP = 8dBm. Assume that the range of the terminal's available spreading factors is [7,12], and select the spreading factor corresponding to the smaller data rate as the terminal's optional spreading factor list listSF i :

[0191] listSF i ={7,8,9,10,11,12}

[0192] Furthermore, the theoretical link budget LM of the terminal is 48.326 dB, LM-3dB=45.326 dB>0, the current modulation bandwidth of the terminal is BW=125 kHz, and the bandwidth continues to increase and can eventually be adjusted to BW=500 kHz, with the remaining LM=42.326 dB.

[0193] Assume that the available bandwidth of the terminal is [62.5kHz, 125kHz, 250kHz, 500kHz], and select the bandwidth corresponding to the smaller data rate as the optional modulation bandwidth list listBW for the terminal i :

[0194] listBW i ={62.5kHz,125kHz,250kHz,500kHz}

[0195] In summary, a list of optional transmit powers and data rates for terminal i under the premise of reachable communication is obtained.

[0196] According to step S104, steps S100 to S103 are repeated to obtain a list of selectable transmit power and data rates for all terminals in the network. Initial values ​​of transmit power and data rate are selected from the list to calculate and initialize network performance indicators. For example, for terminal i, the initial transmit power value is TP = 8 dBm and the initial values ​​of bandwidth and spreading factor are [SF, BW] = [7,500 kHz], corresponding to an initial data rate value of 21.88 kbps.

[0197] For example, assume that there are 50 terminals and 1 gateway deployed in the LoRa network. Among them, the LoRa gateway is deployed above the roof of a building 20m high, and the terminals are deployed in the semi-circular areas of 50m, 150m, 300m, 600m, 1000m, 1300m, 1600m, and 2000m away from the gateway. The spreading factor SF=12 and the modulation bandwidth BW=62.5kHz of all terminals are set, corresponding to the slowest data rate, and the terminal's transmission power is set to the maximum, that is, TP=20dBm. The terminal generates a data packet with a packet length of 20 bytes every 20s on average. Repeat steps S100 to S103, count the link information of each terminal in a fixed time window, calculate and obtain the optional transmission power and data rate list of each terminal in the network under the premise of communication reachability, and select the fastest data rate and corresponding transmission power of each terminal under the premise of communication reachability as the initial value. The initialization network performance indicators obtained using the initial values ​​of terminal data rate and transmission power in the network are: average terminal power consumption E Avg is 2.3993J, the network throughput Γ is 4822.6879bps, and the average terminal delay T Avg It is 1.3993s.

[0198] According to step S105, the performance of the initialized network is evaluated, and an optimization algorithm is used to obtain the optimal data rate and transmission power of each terminal in the network and evaluate the optimal performance of the network. Avg ,Γ,T Avg The weights c1, c2, and c3 are 0.4238, 0.3240, and 0.2522 respectively. After normalizing the indicators, the performance score of the initialized network can be calculated as:

[0199]

[0200] Exemplarily, the above network performance evaluation method is used as the objective function of the network performance optimization problem, and the zebra optimization algorithm is used to solve the optimization problem to obtain the optimal data rate of the terminal in the network. As shown in Table 3, the number of terminals corresponding to different data rates.

[0201] Table 3 Number of terminals corresponding to the parameter combinations of data rates

[0202]

[0203] The LoRa network performance indicators obtained by the above terminal optimal data rate and algorithm are as follows: Terminal average power consumption E Avg is 2.15J, the network throughput Γ is 6683bps, and the average terminal delay T Avg The network performance was evaluated using the combined weighting method, and the optimal performance score of the current network was 72.3681.

[0204] Figure 6 The figure shows a comparison of the packet reception rates of a single terminal under the adaptive data rate and fixed data rate of the present invention. Comparing the average packet reception rates of nodes under the two conditions, the adaptive data rate solution of the present invention improves the packet reception rate by about 33%.

[0205] Figure 7 The figure shows a comparison of the average power consumption of terminals using the adaptive data rate solution of the present invention and other data rate solutions. It can be seen from the figure that the average power consumption of terminals using the adaptive data rate solution of the present invention is lower than that of other solutions.

[0206] Figure 8 The figure shows a comparison of the network throughput and average terminal latency of the adaptive data rate solution of the present invention and other data rate solutions. It can be seen from the figure that the network throughput of the adaptive data rate solution of the present invention is higher than that of other solutions, and the average terminal latency is lower than that of other solutions.

[0207] The data rate control method for terminals in a LoRa network designed in this paper takes into account the terminal's communication link. It uses the link information carried in data packets sent by the terminal to evaluate the terminal's link status through mathematical statistics. This method then obtains a list of possible transmit powers and data rates for the terminal under the premise of reachable communication. The method then calculates network performance indicators and evaluates network performance, taking into account the different data rates used by terminals in the network and the number of terminals using the same data rate. Under the condition of limited terminal power consumption, a network performance optimization model is established and an objective function is determined. An optimization algorithm is then used to determine the transmit power and optimal data rate for each terminal in the network, and the optimal network performance is evaluated.

[0208] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A LoRa network adaptive data rate control method, characterized in that, The following steps are involved: Continuously receive data packets sent by LoRa network terminals and count the link information of received data packets, including the signal-to-noise ratio of the data packets. Signal strength ; Obtain the link information of the LoRa network terminal within a fixed time window, and evaluate the link status of the LoRa network terminal based on the link information; According to the link status of the LoRa network terminal, calculate the signal-to-noise ratio margin and link budget margin of the LoRa network terminal; According to the link information of the LoRa network terminal, the signal-to-noise ratio margin and the link budget margin are combined to obtain the signal-to-noise ratio margin and the theoretical link budget; Based on the signal-to-noise ratio margin and theoretical link budget, calculate the list of optional transmit power and data rates for LoRa network terminals under the premise of reachable communication; Obtain a list of transmit power and data rates available to all terminals in the LoRa network under the premise of reachable communication, and select the initial values ​​of transmit power and data rate from the optional list to calculate the initial network performance indicators; Based on the initial values ​​of transmit power and data rate, combined with the power consumption limit of the LoRa network terminal, the optimal data rate for each terminal is obtained; Based on the adaptive optimal data rate of each terminal, calculate the network performance indicators and evaluate the optimal performance of the LoRa network; Initialize network throughput in network performance indicators , average power consumption of terminals and average terminal delay Perform normalization processing and use the FAHP method to calculate the subjective weight of statistical link information; The objective weights were calculated using the improved CRITIC method and optimized using the VIKOR method; The subjective weight is combined with the optimized objective weight using the multiplication synthesis method to obtain the combined weight. The combined weight and the normalized network performance index are used to obtain the network performance score. , the calculation process of the performance score is the objective function of the optimization problem.

2. A LoRa network adaptive data rate control method according to claim 1, characterized in that, The specific method for continuously receiving data packets sent by the LoRa network terminal and counting the link information of the received data packets is as follows: The LoRa network terminal sends data packets according to the preset transmission power and data rate; The link information of each terminal is collected based on the terminal ID in the received data packet.

3. A LoRa network adaptive data rate control method according to claim 2, characterized in that, Received data packet information, including signal-to-noise ratio, signal strength, and data information; The link information of each terminal includes the signal-to-noise ratio of the data packet Signal strength .

4. A LoRa network adaptive data rate control method according to claim 1, characterized in that, The specific method for obtaining the link information of the LoRa network terminal within a fixed time window and evaluating the link status of the LoRa network terminal based on the link information is as follows: Continuously obtain link information of data packets within a fixed time window and calculate the statistical link information of the data packets sent by the terminal; Use the combined weighting method to evaluate the link status of the terminal.

5. A LoRa network adaptive data rate control method according to claim 4, characterized in that, The specific method of using the combined weighting method to evaluate the link status of the terminal is as follows: Normalize the statistical link information and use the fuzzy analytic hierarchy process to calculate the subjective weight of the statistical link information; The objective weight of statistical link information is calculated using the CRITIC method, and the objective weight is optimized using the VIKOR method; The subjective weight is combined with the optimized objective weight using the multiplication synthesis method to obtain the combined weight. The combined weight and the normalized corresponding statistical link information are used to obtain the terminal link status score.

6. A LoRa network adaptive data rate control method according to claim 1, characterized in that, Based on the signal-to-noise ratio margin and theoretical link budget, the specific method for calculating the list of optional transmit power and data rates for LoRa network terminals under the premise of reachable communication is as follows: Determine the adequacy of link resources based on the signal-to-noise ratio margin. When link resources are redundant, reduce the spreading factor to increase the data rate or reduce the transmit power to reduce power consumption. When link resources are insufficient, increase the transmit power to improve the received signal quality or increase the spreading factor to reduce the data rate. When the theoretical link budget is higher than the preset value, the bandwidth is increased to increase the data rate; when the theoretical link is lower than the preset value, the bandwidth is reduced to reduce the data rate; Based on the signal-to-noise ratio margin and theoretical link budget The value of is used to obtain a list of optional transmit powers and data rates under the premise that the terminal communication is reachable.

7. A LoRa network adaptive data rate control method according to claim 1, characterized in that, Based on the initial values ​​of transmit power and data rate, combined with the power consumption limit of the LoRa network terminal, the specific method for obtaining the optimal data rate for each terminal to adapt is as follows: The initial values ​​of the transmit power and data rate of all terminals in the LoRa network are used as the initial solution to the optimization problem. The Zebra optimization algorithm is used to solve the optimization problem. Starting from the initial solution, the algorithm randomly searches the list of optional transmit power and data rate for all terminals in the LoRa network, and obtains the adaptive data rate that optimizes the performance of the LoRa network under the condition of limited terminal power consumption. The specific method for calculating network performance indicators and evaluating the optimal performance of the LoRa network based on the adaptive optimal data rate of each terminal is as follows: The optimal data rate of each terminal in the LoRa network is adaptive, and the network throughput of the network performance indicator is calculated by combining the transmission power of each terminal in the LoRa network. , average power consumption of terminals and average terminal delay , the combined weighted method is used to obtain the network performance score and complete the optimal performance evaluation of the LoRa network under the condition of limited terminal power consumption.

8. A LoRa network adaptive data rate control system, characterized in that: include: The link information acquisition module is used to continuously receive data packets sent by the LoRa network terminal and count the link information of the received data packets, including the signal-to-noise ratio of the data packets. Signal strength ; The link status acquisition module is used to obtain the link information of the LoRa network terminal within a fixed time window and evaluate the link status of the LoRa network terminal based on the link information; The rate list acquisition module is used to calculate the signal-to-noise ratio margin and link budget margin of the LoRa network terminal based on the link status of the LoRa network terminal; based on the link information of the LoRa network terminal, combined with the signal-to-noise ratio margin and link budget margin, the signal-to-noise ratio margin and theoretical link budget are obtained; based on the signal-to-noise ratio margin and theoretical link budget, the optional transmission power and data rate list of the LoRa network terminal under the premise of reachable communication is calculated; The performance index acquisition module is used to obtain a list of optional transmit power and data rate for all terminals in the LoRa network under the premise of reachable communication, and select the initial values ​​of transmit power and data rate from the optional list to calculate the initial network performance index; The optimal rate acquisition module is used to obtain the optimal data rate of each terminal based on the initial values ​​of the transmission power and data rate, combined with the power consumption limit of the LoRa network terminal; based on the optimal data rate of each terminal, calculate the network performance index and evaluate the optimal performance of the LoRa network; initialize the network throughput in the network performance index , average power consumption of terminals and average terminal delay Perform normalization processing and use the FAHP method to calculate the subjective weight of statistical link information; The objective weights were calculated using the improved CRITIC method and optimized using the VIKOR method; The subjective weight is combined with the optimized objective weight using the multiplication synthesis method to obtain the combined weight. The combined weight and the normalized network performance index are used to obtain the network performance score. , the calculation process of the performance score is the objective function of the optimization problem.

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