LoRa antenna coverage intelligent evaluation and optimization system for smart city

Abstract

The application discloses a LoRa antenna coverage intelligent evaluation and optimization system for a smart city, relates to the technical field of LoRa antennas, and comprises a coverage module, an adjustment module and a signal module. In the application, the coverage edge position of the LoRa antenna can be accurately evaluated, resource waste caused by insufficient signal coverage or excessive coverage can be avoided, a relay node is installed for a grid point with a signal strength lower than a threshold value, signal strength compensation can be performed on the coverage edge position, future traffic volume can be predicted, channel resources can be planned in advance, channel resources or network configuration can be adjusted in advance according to the prediction result, the power threshold value can be dynamically adjusted according to the load rate of the LoRa antenna, the stability of the signal is maintained, retransmission and errors caused by unstable signals are reduced, and the overall communication efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of LoRa antenna technology, and in particular to a smart evaluation and optimization system for LoRa antenna coverage in smart cities. Background Technology

[0002] In the construction of smart cities, LoRa (LongRange) technology has been widely used in the field of Internet of Things (IoT) communication due to its advantages such as low power consumption and long-distance transmission. The coverage effect of LoRa antennas directly affects the stable operation of various smart city services. With the continuous expansion of city scale and the rapid increase in the number of IoT devices, the requirements for LoRa antenna coverage, signal strength, and channel resource allocation are becoming increasingly stringent.

[0003] Currently, in existing technologies, the evaluation and optimization of LoRa antenna coverage mainly rely on manual experience and simple signal testing equipment. In terms of signal strength testing, there is often a lack of systematic and comprehensive testing methods, making it impossible to accurately determine the coverage edge location. This results in weak or even no signal coverage in some areas, affecting the normal communication of IoT devices. In terms of channel resource allocation, it is impossible to dynamically adjust according to the traffic volume in different areas and times, resulting in wasted or insufficient channel resources and reduced communication efficiency. In addition, it is difficult to adaptively adjust the transmission power according to the load status of the LoRa antenna, resulting in signal strength fluctuations. Signal fluctuations make the signal quality unstable, sometimes too strong and sometimes too weak, affecting the accurate transmission of data.

[0004] Therefore, a smart evaluation and optimization system for LoRa antenna coverage in smart cities is proposed to address the above problems. Summary of the Invention

[0005] The main objective of this invention is to provide a smart evaluation and optimization system for LoRa antenna coverage in smart cities, in order to solve the problems mentioned in the background above.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is: a LoRa antenna coverage intelligent evaluation and optimization system for smart cities, the system comprising a coverage module, an adjustment module, and a signal module;

[0007] The coverage module is used to divide the coverage area of ​​the LoRa antenna into multiple small grids, place signal strength testers at multiple grid points, and gradually expand the test range away from the center of the LoRa antenna to perform signal strength tests, determine the coverage edge position of the LoRa antenna, and perform signal strength compensation at the coverage edge position.

[0008] The adjustment module is used to conduct low-load, medium-load, and high-load communication tests at grid points on the coverage edge using a test terminal, to evaluate the performance of the LoRa antenna under various loads, dynamically allocate channel resources according to the traffic volume at different times, and predict channel resource requirements based on historical test data and traffic patterns.

[0009] The signal module is used to receive the signal from the LoRa antenna in real time through a spectrum analyzer, calculate the signal-to-noise ratio, compare it with a set power threshold, determine whether to adjust the transmission power, and adaptively and dynamically adjust the power threshold according to the load status of the LoRa antenna.

[0010] Furthermore, the coverage module includes an arrangement unit, an analysis unit, and a compensation unit;

[0011] The arrangement unit is used to divide the coverage area of ​​the LoRa antenna into multiple small grids and arrange signal strength testers at multiple grid points. Starting from the grid point closest to the center of the LoRa antenna, the signal strength tester is started, and the signal strength is measured according to the set test parameters. The test data of each grid point is recorded, and the process is gradually expanded to the direction away from the center of the antenna to perform signal strength tests on the new grid points.

[0012] Furthermore, the analysis unit is used to collect signal strength test data of all grid points, draw a signal strength distribution map using Excel, and set a signal strength threshold PT. At the same time, the signal strength test data of all grid points are compared with the set signal strength threshold PT. If the signal strength data is lower than the signal strength threshold PT, the grid point is marked, and the grid points at the edge of the signal strength distribution map are connected.

[0013] Furthermore, the compensation unit is used to install relay nodes at grid points in the signal strength distribution map where the signal strength test is lower than a set signal strength threshold PT.

[0014] Furthermore, the adjustment module includes a load assessment unit, an intelligent allocation unit, and a prediction unit.

[0015] Furthermore, the load assessment unit is used to transmit signals multiple times through the test terminal and receive them through the LoRa antenna, collect actual successfully received data, and calculate the data reception rate. The calculation formula is as follows:

[0016] ;

[0017] in, Represents data reception rate. Represents the actual number of times a signal was transmitted. This represents the actual successful reception of data; by setting the number of transmission signals N-10, N, and N+10 under low, medium, and high loads, the performance of the LoRa antenna under various loads is evaluated.

[0018] Furthermore, the intelligent allocation unit is used by the data acquisition instrument to collect the traffic volume of the covered area in the morning, noon, and evening, and calculate the channel allocation function for the corresponding time period, as well as the number of channels allocated for the corresponding time period. The calculation steps are as follows:

[0019] Step 1: Calculate the channel allocation function. The calculation formula is as follows:

[0020] ;

[0021] in, Represents the channel allocation ratio function. The representative region's business volume during time period t, where time period t is selected as either morning, noon, or evening.

[0022] Step 2, calculate the number of allocated channels, using the following formula:

[0023] ;

[0024] in, The number of channels allocated to a region within time period t. This represents the number of available channels, and the time period t is selected from early morning, noon, or evening.

[0025] Furthermore, the prediction unit predicts future morning, noon, and evening traffic volumes based on historical morning, noon, and evening traffic volumes, using the following calculation formula:

[0026] ;

[0027] in, This represents the region's business volume during one of the following time periods: morning, noon, or evening. The representative region's business volume within one of the following time periods, t-1, is in the morning, noon, or evening; n represents the number of data points used to calculate past data.

[0028] Among them The channel demand is then incorporated into the intelligent allocation unit to predict one of the following time periods: morning, noon, or evening.

[0029] Furthermore, the signal module includes a receiving unit, a comparison unit, and an adaptive unit;

[0030] The receiving unit is used to receive and store the signals from the LoRa antenna in real time using a spectrum analyzer;

[0031] The comparison unit is used to calculate the signal-to-noise ratio of the received signal data in real time, and to compare it with a set power threshold to determine whether to adjust the transmission power.

[0032] Furthermore, the adaptive unit is used to calculate the load rate of the LoRa antenna in real time and dynamically adjust the power threshold, as follows:

[0033] Step 1: Calculate the load factor of the LoRa antenna in real time. The calculation formula is as follows:

[0034] ;

[0035] in, Represents load rate. Represents the total number of antenna nodes. This represents the number of nodes that are currently active.

[0036] Step two, dynamically adjust the power threshold, and calculate it using the following formula:

[0037] ;

[0038] in, This represents the adaptively adjusted power threshold. Represents the adjustment coefficient. Represents the reference load rate. Represents the initial power threshold. This represents the load rate.

[0039] The present invention has the following beneficial effects:

[0040] 1. In this invention, by setting up a coverage module, the LoRa antenna coverage area can be divided into grids and test instruments can be arranged during the evaluation of LoRa antennas. The test range can be gradually expanded from near the center of the antenna, which can accurately measure the signal strength at different locations and assist in the signal strength distribution map. This allows for accurate evaluation of the coverage edge position of the LoRa antenna, providing a reliable basis for subsequent optimization and avoiding resource waste caused by insufficient or excessive signal coverage. Furthermore, by installing relay nodes at grid points where the signal strength is below the threshold, signal strength compensation can be performed at the coverage edge position, effectively improving the communication quality in areas with weak signals, enhancing the signal coverage effect and stability of the entire network, meeting the stable and reliable communication needs of various devices in smart cities, and ensuring the efficient operation of the system.

[0041] 2. In this invention, by setting an adjustment module, the load assessment unit can transmit and receive signals multiple times and calculate the data reception rate during the evaluation of the LoRa antenna, accurately assessing the performance of the LoRa antenna under different loads. This facilitates the subsequent rational allocation of channel resources. The intelligent allocation unit calculates the channel allocation function and the number of channels allocated based on the traffic volume data collected at different time periods, enabling the rational allocation of channel resources, ensuring smooth data transmission and avoiding resource waste. The prediction unit predicts future traffic volume based on historical traffic volume data, enabling advance planning of channel resources. Based on the prediction results, the system can increase channel resources or adjust network configuration in advance before traffic volume increases, avoiding communication bottlenecks caused by insufficient resources and improving the system's service quality.

[0042] 3. In this invention, by setting a signal module, the receiving unit can collect and store signal data in real time during the evaluation of the LoRa antenna. This allows for the complete recording of various signal characteristics and changes. The comparison unit calculates the signal-to-noise ratio in real time and compares it with a set power threshold to determine whether to adjust the transmission power. This timely adjustment of the transmission power avoids signal problems caused by excessively high or low power. The adaptive unit calculates the load rate of the LoRa antenna in real time and dynamically adjusts the power threshold according to the load rate to maintain signal stability, reduce retransmissions and errors caused by signal instability, and improve overall communication efficiency. Attached Figure Description

[0043] Figure 1 This is a flowchart of the LoRa antenna coverage intelligent assessment and optimization system for smart cities according to the present invention;

[0044] Figure 2 This is an overall framework diagram of the LoRa antenna coverage intelligent evaluation and optimization system for smart cities according to the present invention. Detailed Implementation

[0045] 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.

[0046] Implementation 1, please refer to Figure 1 and Figure 2 The present invention provides a technical solution: a LoRa antenna coverage intelligent evaluation and optimization system for smart cities, the system including a coverage module, an adjustment module and a signal module;

[0047] The coverage module is used to divide the coverage area of ​​the LoRa antenna into multiple small grids, place signal strength testers at multiple grid points, and gradually expand the test range away from the center of the LoRa antenna to perform signal strength tests, determine the coverage edge position of the LoRa antenna, and perform signal strength compensation at the coverage edge position.

[0048] The adjustment module is used to conduct low-load, medium-load, and high-load communication tests at grid points on the coverage edge through the test terminal, evaluate the performance of LoRa antenna under various loads, dynamically allocate channel resources according to the traffic volume at different times, and predict channel resource requirements based on historical test data and traffic patterns.

[0049] The signal module is used to receive the signal from the LoRa antenna in real time through a spectrum analyzer, calculate the signal-to-noise ratio, compare it with a set power threshold, determine whether to adjust the transmit power, and adaptively and dynamically adjust the power threshold according to the load status of the LoRa antenna.

[0050] The coverage module includes layout units, analysis units, and compensation units;

[0051] The deployment unit is used to divide the coverage area of ​​the LoRa antenna into multiple small grids and deploy signal strength testers at multiple grid points. Starting from the grid point closest to the center of the LoRa antenna, the signal strength tester is activated, and the signal strength is measured according to the set test parameters. The test data of each grid point is recorded, and the process is gradually expanded to the direction away from the center of the antenna to perform signal strength tests on new grid points.

[0052] The analysis unit is used to collect signal strength test data of all grid points, draw a signal strength distribution map using Excel, and set a signal strength threshold PT. At the same time, the signal strength test data of all grid points are compared with the set signal strength threshold PT. If the signal strength is lower than the signal strength threshold PT, the grid point is marked, and the grid points at the edge of the signal strength distribution map are connected.

[0053] Specifically, the signal strength threshold PT is set as the minimum signal strength required for normal communication of existing LoRa devices. When the signal strength test data of a grid point is greater than the threshold, it continues to spread outward. When the signal strength test data of a grid point is less than or equal to the set threshold, it is marked.

[0054] The compensation unit is used to install relay nodes at grid points in the signal strength distribution map where the signal strength test is lower than the set signal strength threshold PT.

[0055] In this embodiment, the LoRa antenna coverage area is divided into grids and test instruments are arranged in the deployment unit. The test range is gradually expanded from near the center of the antenna, which can accurately measure the signal strength at different locations and assist in the signal strength distribution map. This allows for accurate assessment of the coverage edge position of the LoRa antenna, providing a reliable basis for subsequent optimization and avoiding resource waste caused by insufficient or excessive signal coverage. Relay nodes are installed at grid points where the signal strength is below the threshold to compensate for the signal strength at the coverage edge position, effectively improving the communication quality in areas with weak signals, enhancing the signal coverage effect and stability of the entire network, meeting the stable and reliable communication needs of various devices in smart cities, and ensuring the efficient operation of the system.

[0056] Implementation 2, please refer to Figure 1 and Figure 2 The present invention provides a technical solution: based on the first embodiment, the adjustment module includes a load assessment unit, an intelligent allocation unit, and a prediction unit.

[0057] The load assessment unit is used to transmit signals multiple times through the test terminal and receive them via the LoRa antenna, collect the actual successfully received data, and calculate the data reception rate. The calculation formula is as follows:

[0058] ;

[0059] in, Represents data reception rate. Represents the actual number of times a signal was transmitted. This represents the actual successful reception of data; by setting the number of transmission signals N-10, N, and N+10 under low, medium, and high loads, the performance of the LoRa antenna under various loads is evaluated.

[0060] Specifically, a data reception rate of 60% or higher indicates high performance under the corresponding load, while a data reception rate of less than 60% indicates low performance under the same load. Through extensive practice and research, the industry has gradually established a reference standard for data reception rate. In most practical application scenarios, when the data reception rate reaches 60% or higher, the accuracy and stability of data transmission between devices can meet common business needs and ensure the basic performance of the communication system.

[0061] The intelligent allocation unit is used by the data acquisition instrument to collect the traffic volume of the covered area in the morning, noon and evening, and calculate the channel allocation function for the corresponding time period, as well as the number of channels allocated for the corresponding time period. The calculation steps are as follows:

[0062] Step 1: Calculate the channel allocation function. The calculation formula is as follows:

[0063] ;

[0064] in, Represents the channel allocation ratio function. The representative region's business volume during time period t, where time period t is selected as either morning, noon, or evening.

[0065] Step 2, calculate the number of allocated channels, using the following formula:

[0066] ;

[0067] in, The number of channels allocated to a region within time period t. This represents the number of available channels, and the time period t is selected from early morning, noon, or evening.

[0068] Specifically, by substituting the traffic volume of different time periods (morning, noon, and evening) into the formulas in steps one and two, the number of channels allocated for different time periods can be calculated.

[0069] The forecasting unit predicts future morning, noon, and evening traffic volumes based on historical morning, noon, and evening traffic volumes. The calculation formula is as follows:

[0070] ;

[0071] in, This represents the region's business volume during one of the following time periods: morning, noon, or evening. The representative region's business volume within one of the following time periods, t-1, is in the morning, noon, or evening; n represents the number of data points used to calculate past data.

[0072] Among them The channel demand is then incorporated into the intelligent allocation unit to predict one of the following time periods: morning, noon, or evening.

[0073] Specifically, regarding future business volume The traffic volume of the current region within time period t in step 1 of replacing the intelligent allocation unit It calculates the future channel allocation ratio function, thereby predicting future channel demand in advance, which facilitates the planning of channel resources, and the time period includes three time periods: morning, noon and evening.

[0074] In this embodiment, the load assessment unit transmits and receives signals multiple times and calculates the data reception rate to accurately evaluate the performance of the LoRa antenna under different loads, facilitating the subsequent rational allocation of channel resources. The intelligent allocation unit calculates the channel allocation function and the number of channels allocated based on the traffic volume data collected in different time periods, enabling the rational allocation of channel resources, ensuring smooth data transmission and avoiding resource waste. The prediction unit predicts future traffic volume based on historical traffic volume data, enabling advance planning of channel resources. Based on the prediction results, the system can increase channel resources or adjust network configuration in advance before traffic volume increases, avoiding communication bottlenecks caused by insufficient resources and improving the system's service quality.

[0075] Implementation 3, please refer to Figure 1 and Figure 2 The present invention provides a technical solution: based on embodiment one, the signal module includes a receiving unit, a comparison unit and an adaptive unit;

[0076] The receiving unit is used to receive and store the signals from the LoRa antenna in real time via a spectrum analyzer;

[0077] Specifically, the spectrum analyzer receives and collects signal data including noise power. Signal power 1 and the number of nodes currently active, E.

[0078] The comparison unit is used to calculate the signal-to-noise ratio of the received signal data in real time, and to compare it with the set power threshold to determine whether to adjust the transmission power.

[0079] Specifically, the signal-to-noise ratio (SNR) calculation formula is as follows: ;in, Represents the signal-to-noise ratio. Represents noise power. 1 represents information power; the signal-to-noise ratio is calculated. With the set initial power threshold Compare the signal-to-noise ratios. Greater than or equal to the initial power threshold When the signal-to-noise ratio is low, the LoRa antenna's transmit power remains constant or is reduced via the LoRa RF module. Greater than or equal to the initial power threshold If the signal quality is poor, the transmission power will be increased by using the LoRa RF module.

[0080] The adaptive unit is used to calculate the load rate of the LoRa antenna in real time and dynamically adjust the power threshold. The steps are as follows:

[0081] Step 1: Calculate the load factor of the LoRa antenna in real time. The calculation formula is as follows:

[0082] ;

[0083] in, Represents load rate. Represents the total number of antenna nodes. This represents the number of nodes that are currently active.

[0084] Step two, dynamically adjust the power threshold, and calculate it using the following formula:

[0085] ;

[0086] in, This represents the adaptively adjusted power threshold. Represents the adjustment coefficient. Represents the reference load rate. Represents the initial power threshold. This represents the load rate.

[0087] Specifically, the initial power threshold should be set with reference to the device's own performance parameters to ensure that the threshold is set within the power range that the device can support.

[0088] In this embodiment, the receiving unit collects and stores signal data in real time, which can completely record various characteristics and changes of the signal. The comparison unit calculates the signal-to-noise ratio in real time and compares it with the set power threshold to determine whether to adjust the transmission power, thereby adjusting the transmission power in a timely manner to avoid signal problems caused by excessive or insufficient power. The adaptive unit calculates the load rate of the LoRa antenna in real time and dynamically adjusts the power threshold according to the load rate to maintain signal stability, reduce retransmissions and errors caused by signal instability, and improve overall communication efficiency.

[0089] In this invention, a smart evaluation and optimization system for LoRa antenna coverage in smart cities, by setting up a coverage module, can accurately measure the signal strength at different locations by dividing the LoRa antenna coverage area into a grid and deploying testing instruments, gradually expanding the test range from near the antenna center during LoRa antenna evaluation. This provides a reliable basis for evaluating the coverage edge location of the LoRa antenna, supplemented by a signal strength distribution map, thus accurately assessing the coverage edge location and avoiding resource waste due to insufficient or excessive signal coverage. Furthermore, by installing relay nodes at grid points with signal strength below a threshold, signal strength compensation can be performed at the coverage edge location, effectively improving communication quality in weak signal areas, enhancing the overall network signal coverage and stability, meeting the stable and reliable communication needs of various devices in smart cities, and ensuring efficient system operation. The system also utilizes a load evaluation unit to repeatedly transmit and receive signals and calculate the data reception rate, accurately evaluating the LoRa antenna performance under different loads, facilitating subsequent reasonable allocation of resources. The intelligent allocation unit calculates the channel allocation function and the number of channels allocated based on the collected traffic data, enabling reasonable allocation of channel resources, ensuring smooth data transmission and avoiding resource waste. The prediction unit predicts future traffic based on historical traffic data, allowing for advance planning of channel resources. Based on the prediction results, the system can increase channel resources or adjust network configuration in advance before traffic growth, avoiding communication bottlenecks caused by insufficient resources and improving the system's service quality. The receiving unit collects and stores signal data in real time, completely recording various characteristics and changes of the signal. The comparison unit calculates the signal-to-noise ratio in real time and compares it with a set power threshold to determine whether to adjust the transmit power, thereby adjusting the transmit power in a timely manner to avoid signal problems caused by excessive or insufficient power. The adaptive unit calculates the load rate of the LoRa antenna in real time and dynamically adjusts the power threshold according to the load rate to maintain signal stability, reduce retransmissions and errors caused by signal instability, and improve overall communication efficiency.

[0090] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0091] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1.A LoRa antenna coverage intelligent evaluation and optimization system for smart city, characterized in that, The system comprises a coverage module, an adjustment module and a signal module; The coverage module is used for dividing the coverage area of the LoRa antenna into multiple small grids, arranging signal strength testers at multiple grid points, expanding the test range by gradually moving away from the center of the LoRa antenna, performing signal strength test, determining the coverage edge position of the LoRa antenna, and compensating the signal strength at the coverage edge position; The adjustment module is used for performing low-load, medium-load and high-load communication test at the grid points on the coverage edge by the test terminal, evaluating the performance of the LoRa antenna under various loads, dynamically allocating channel resources according to the traffic volume at different times, and predicting the channel resource demand according to historical test data and traffic rules; The signal module is used for receiving the signal of the LoRa antenna in real time by the spectrum analyzer, calculating the signal-to-noise ratio, comparing with the set power threshold, determining whether to adjust the transmission power, and adaptively adjusting the power threshold according to the load state of the LoRa antenna; The adjustment module comprises a load evaluation unit, an intelligent allocation unit and a prediction unit; The load evaluation unit is used for transmitting multiple signals by the test terminal and receiving them by the LoRa antenna, collecting actual successful reception data, calculating the data reception rate, and the calculation formula is as follows: ； wherein, representing the data receiving rate, representing the actual number of transmitted signals, representing the actual successful received data; by setting the number of transmitted signals N-10, N and N+10 of low load, medium load and high load, the performance of LoRa antenna under various loads is evaluated; The intelligent allocation unit is used for collecting the early, medium and late traffic volume of the coverage area by the data acquisition instrument, calculating the channel allocation function of the corresponding time period, and allocating the corresponding channel number of the corresponding time period, and the calculation steps are as follows: Step 1, calculating the channel allocation function, the calculation formula is as follows: ； wherein, representing a channel allocation proportion function, representing the traffic volume of the region at a time period t, the time period t being selected from one of early, mid and late. Step 2, calculating the allocated channel number, the calculation formula is as follows: ； wherein, a number of channels allocated to the representative area in a time period t, a number of available channels, the time period t being selected from one of early, mid and late. The prediction unit predicts the future early, medium and late traffic volume based on the historical early, medium and late traffic volume, and the calculation formula is as follows: ； wherein, the amount of traffic in the future in one of the time periods early, mid and late, the amount of traffic in the future in one of the time periods early, mid and late, n representing the number of past data taken into account. wherein the into the intelligent allocation unit, predicting the channel demand for one of the future early, mid, and late time periods. 2.The LoRa antenna coverage intelligent evaluation and optimization system for smart city according to claim 1, wherein, The coverage module comprises a layout unit, an analysis unit and a compensation unit; The layout unit is used for dividing the coverage area of the LoRa antenna into multiple small grids, arranging signal strength testers at multiple grid points, starting the signal strength tester at the grid point close to the center of the LoRa antenna, measuring the signal strength according to the set test parameters, recording the test data of each grid point, and gradually expanding to the grid points away from the center of the antenna. 3.The LoRa antenna coverage intelligent evaluation and optimization system for smart city according to claim 2, wherein, The analysis unit is used for collecting the signal strength test data of all grid points, drawing a signal strength distribution map by Excel, setting a signal strength threshold PT, comparing all grid point signal strength test data with the set signal strength threshold PT, marking the grid point if it is lower than the signal strength threshold PT, and connecting the grid points on the edge of the signal strength distribution map. 4.The LoRa antenna coverage intelligent evaluation and optimization system for smart city according to claim 3, wherein, The compensation unit is used for installing a relay node at the grid point in the signal strength distribution map whose signal strength test is lower than the set signal strength threshold PT. 5.The LoRa antenna coverage smart evaluation and optimization system for smart city of claim 1, wherein, The signal module comprises a receiving unit, a comparison unit and an adaptive unit; The receiving unit is used for receiving and storing the signal of the LoRa antenna in real time by the spectrum analyzer; The comparison unit is used for calculating the signal-to-noise ratio of the real-time received signal data, and comparing with the set power threshold to judge whether to adjust the transmitting power. 6.The LoRa antenna coverage smart evaluation and optimization system for smart city according to claim 5, wherein, The adaptive unit is used for real-time calculation of the load rate of the LoRa antenna, and dynamic adjustment of the power threshold, with the following steps: Step one, real-time calculation of the load rate of the LoRa antenna, with the following calculation formula: ； wherein, represents the load rate, represents the total number of antenna nodes, represents the number of nodes currently in an active state; Step two, dynamic adjustment of the power threshold, with the following calculation formula: ； wherein, represents an adaptively adjusted power threshold, represents an adjustment coefficient, represents a reference load rate, represents an initial power threshold, represents a load rate.

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