An airborne base station communication coverage test method and system for emergency communication

Abstract

The application discloses an airborne base station communication coverage test method and system for emergency communication, belongs to the technical field of communication coverage evaluation, adopts a lightweight test architecture to execute a hierarchical test procedure on the airborne base station based on a four-dimensional coverage index system of dynamic environment double adaptation, collects various coverage performance data under the four-dimensional coverage index system through the lightweight test architecture, synchronously collects flight parameters, positioning information and environmental parameters of the airborne base station at each test link of the hierarchical test procedure, compares the coverage performance data with preset threshold values, and completes index verification; the four-dimensional coverage index system comprises dynamic coverage strength indexes, dynamic link quality indexes, multi-user concurrent performance indexes and extreme environment adaptation indexes; the hierarchical test procedure comprises single-user dynamic test, multi-user concurrent test, extreme environment simulation test and scenario verification test.

Description

Technical Field

[0001] This invention belongs to the field of communication coverage assessment technology, specifically relating to an airborne base station communication coverage testing method and system for emergency communication. Background Technology

[0002] With the rapid development of the low-altitude economy and the demand for emergency communications, airborne base stations have become key equipment for compensating for insufficient ground network coverage and building an integrated air-ground emergency communication network. In extreme scenarios where natural disasters such as earthquakes, floods, and landslides cause the disruption of roads, power, and communications, traditional emergency communication methods such as ground communication vehicles and portable base stations are limited in deployment and coverage, making it difficult to meet the communication support needs during the critical rescue period. Airborne base stations, using drones and large unmanned helicopters as carriers, have advantages such as rapid response, high-altitude loiter capability, mobility, and no terrain limitations. They can quickly take off to fill communication blind spots and have demonstrated significant application value in numerous real-world rescue operations.

[0003] Currently, communication coverage assessment and testing technologies for airborne base stations still have significant limitations, making it difficult to adapt to their dynamic operating characteristics and the stringent requirements of emergency scenarios: First, the assessment models are statically fixed, resulting in poor dynamic and environmental adaptability. Existing coverage models are mostly based on fixed base station designs, failing to fully consider the three-dimensional dynamic characteristics of airborne base stations at flight altitudes of 500–5000 meters and moving speeds of 200–800 km / h. They also fail to effectively integrate complex environmental parameters such as rainfall, dense smoke, low temperatures, and terrain obstruction, using only simplified path loss models, which easily leads to distorted coverage characterization, inaccurate assessment of low-altitude blind spots, and significant deviations in signal attenuation assessment under extreme environments. Second, the testing process is cumbersome and cannot meet the timeliness requirements of emergency response. Traditional ground testing relies on low-speed manual road testing, which is time-consuming and inefficient; satellite communication testing requires the collaboration of multiple ground stations, with a cycle that can last for several weeks, neither of which can meet the emergency response requirements for rapid verification of core areas within 4 hours after a disaster. At the same time, the testing equipment lacks calibration mechanisms designed for extreme temperature and humidity, low visibility, and other scenarios, making it difficult to guarantee data integrity and accuracy. Third, the assessment dimensions are singular and disconnected from actual emergency operations. Existing evaluation systems tend to focus on static parameters such as signal strength and block error rate, lacking quantitative indicators for dynamic performance such as coverage continuity, high-speed handover stability, and service interruption recovery time. This makes it difficult to accurately support low-latency, high-reliability emergency services such as command and dispatch and data transmission, and can easily lead to the problem of "meeting the indicators but having a poor communication experience".

[0004] In summary, existing communication coverage assessment technologies are mostly geared towards fixed scenarios or traditional emergency needs, and generally suffer from insufficient dynamic adaptation, lack of adaptation to extreme environments, low testing efficiency, and one-sided assessment dimensions. These limitations fail to meet the reliable deployment and performance verification requirements of airborne base stations in emergency rescue scenarios, thus hindering the practical application and promotion of integrated air-ground-space emergency communication networks. Therefore, there is an urgent need for a communication coverage testing method and system that adapts to the dynamic characteristics of airborne base stations and takes into account both extreme environments and emergency response timeliness. Summary of the Invention

[0005] The purpose of this invention is to overcome the problem that existing communication coverage assessment technologies cannot meet the needs of airborne base stations in emergency rescue scenarios, and to propose an airborne base station communication coverage testing method and system for emergency communication.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for testing the communication coverage of an airborne base station for emergency communication, comprising the following steps: S1. For the airborne base station to be tested, configure the coverage performance evaluation benchmark parameters. The benchmark parameters include a four-dimensional coverage index set for dynamic environment dual adaptation, and the corresponding qualification threshold for each index. The four-dimensional coverage index set includes dynamic coverage strength index, dynamic link quality index, multi-user concurrent performance index, and extreme environment adaptation index. S2. Perform communication coverage testing on the airborne base station. During the test, simultaneously collect the real-time flight positioning parameters of the airborne base station, the environmental parameters of the test scenario, and the communication coverage performance data corresponding to the four-dimensional coverage index set. S3. Based on the qualified threshold configured in step S1, perform compliance verification on the communication coverage performance data collected in S2, and output the test results of the airborne base station communication coverage performance.

[0007] Furthermore, in step S1, the dynamic coverage strength indicators include time-averaged reference signal received power and interference immunity reference signal received power. Dynamic link quality metrics include dynamic signal-to-interference-plus-noise ratio, dynamic block error rate, and signal penetration rate; Multi-user concurrent performance metrics include regional user access success rate and handover interruption duration; extreme environment adaptability metrics include environmental adaptability coefficient and equipment calibration deviation.

[0008] Furthermore, in step S2, when collecting basic data on the received power of the anti-interference reference signal, environmental parameters such as rainfall intensity, terrain type, and visibility of dense smoke are collected simultaneously to calculate the received power of the anti-interference reference signal after superimposed rainfall attenuation compensation, terrain occlusion compensation, and dense smoke attenuation compensation; when calculating the dynamic signal to interference plus noise ratio, Doppler frequency shift compensation is introduced.

[0009] Furthermore, in step S2, when performing communication coverage testing on the airborne base station, a progressive layered testing process is adopted, sequentially performing single-user dynamic testing, multi-user concurrent testing, extreme environment simulation testing, and scenario-based verification testing, and synchronously collecting corresponding parameters and communication coverage performance data in each test stage.

[0010] Furthermore, the single-user dynamic test includes: a preset flight profile, which includes multiple flight altitude levels and flight speed levels; controlling the airborne base station to fly according to the preset flight profile; collecting dynamic coverage strength index data according to a preset spatial sampling interval; and collecting dynamic link quality index data according to a preset time window. Multi-user concurrent testing includes setting multiple user density levels, configuring a mixed service model consisting of voice, video, and data services in a preset ratio, initiating concurrent services sequentially according to user density levels, and collecting corresponding communication coverage performance data.

[0011] Furthermore, the extreme environment simulation test includes first setting extreme scenario parameters, completing the test equipment calibration according to the preset environmental calibration coefficient mapping table, and then controlling the airborne base station to operate according to the preset flight profile and collecting full index data. Scenario-based verification testing includes first performing static benchmark tests to establish performance benchmark values, and then performing dynamic boundary tests to collect coverage continuity and switching performance data, thus completing full-scenario data collection.

[0012] Furthermore, the test results output in step S3 include adjusting the beam pointing, transmit power, or corresponding environmental compensation coefficient of the airborne base station when the indicators fail to meet the standards, and re-executing the test steps corresponding to the failed indicators until all indicators meet the qualified threshold requirements, and outputting the final test results; wherein, the beam pointing is adjusted according to a preset angle step size, and the transmit power is adjusted within a preset range according to a preset power step size.

[0013] Furthermore, during the compliance verification in step S3, the 3σ criterion is used to preprocess the communication coverage performance data collected in S2 to remove outliers.

[0014] Secondly, the present invention provides an airborne base station communication coverage testing system for emergency communication, which is used to implement an airborne base station communication coverage testing method for emergency communication, including a parameter configuration module for configuring coverage performance evaluation benchmark parameters; The test execution module is used to perform communication coverage tests on airborne base stations. The data acquisition module is used to synchronously collect real-time flight positioning parameters, environmental parameters, and communication coverage performance data during the test. The indicator verification module is used to verify the compliance of communication coverage performance data and output the test results.

[0015] Furthermore, it also includes a closed-loop optimization module, which is used to adjust the corresponding parameters of the airborne base station and trigger a retest when an indicator fails to meet the standard.

[0016] Compared with the prior art, the present invention has the following beneficial technical effects: This invention proposes an airborne base station communication coverage testing method for emergency communications, breaking through the limitations of existing static evaluation frameworks, single-scenario adaptation, and the gap in extreme environment evaluation. It constructs a coverage evaluation technology system adapted to the dynamic characteristics of airborne base stations and the needs of emergency scenarios, establishing a dynamic-environment dual-adaptation evaluation model that integrates the flight status of the airborne base station and environmental parameters. Based on the 3GPP propagation model, it performs scenario-based corrections, achieving real-time prediction of coverage range and accurate blind spot identification. It can control the coverage estimation deviation in extreme environments to within 5%, and the blind spot identification accuracy rate is ≥95%. Furthermore, it develops an efficient and extreme-environment-adaptive testing scheme, designs a lightweight testing system, simplifies the deployment process, and can simultaneously test for temperatures ranging from -40℃ to 60℃ and rainfall rates from 0 to 25 mm / h. A dedicated calibration scheme is developed for visibility scenarios of 0-500m, controlling equipment testing errors within ±1dB to meet the timeliness requirements of emergency response. A multi-dimensional quantitative evaluation system is constructed, breaking through the limitations of existing static parameter-dominated systems. New core dimensions such as dynamic coverage strength, dynamic link quality, multi-user concurrent performance, and extreme environment adaptability are added, strengthening the correlation between indicators and service quality, clarifying differentiated coverage thresholds for different services, and ensuring service continuity in high-speed mobile scenarios. The dynamic adjustment mechanism is optimized, employing non-intelligent joint optimization methods such as dynamic beam adjustment and adaptive power configuration. This allows for rapid response to environmental changes and flight status adjustments without relying on algorithm modeling, reducing handover latency to within 15ms and improving system anti-interference capabilities and communication reliability. Through the achievement of these objectives, this invention systematically solves the four core problems of existing technologies in airborne base station coverage evaluation: inaccurate measurement, low efficiency, poor assurance, and weak anti-interference. It provides standardized and implementable technical support for the efficient deployment and reliable operation of airborne base stations in extreme emergency and low-altitude operation scenarios. Attached Figure Description

[0017] The accompanying drawings are provided to further understand the invention and constitute a part of this invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0018] Figure 1 This is a schematic diagram of the direct access mode for drone base stations.

[0019] Figure 2 This is a schematic diagram of the drone base station relay access mode.

[0020] Figure 3A block diagram of airborne communication coverage indicators.

[0021] Figure 4 This is a flowchart for a single-user dynamic testing process.

[0022] Figure 5 Flowchart for multi-user concurrent testing.

[0023] Figure 6 This is a flowchart for extreme environment simulation testing.

[0024] Figure 7 This is a flowchart for scenario-based verification testing.

[0025] Figure 8 This is a flowchart of an airborne base station communication coverage testing method for emergency communication according to the present invention.

[0026] Figure 9 This is a simplified structural diagram of an airborne base station communication coverage testing system for emergency communication according to the present invention. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0028] It should be noted that when an element is referred to as being "set on" another element, it can be directly on the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only embodiments.

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0031] Example 1 See Figure 8 A method for testing communication coverage of an airborne base station for emergency communications includes the following steps: S1. For the airborne base station to be tested, configure the coverage performance evaluation benchmark parameters. The benchmark parameters include a four-dimensional coverage index set for dynamic environment dual adaptation, and the corresponding qualification threshold for each index. The four-dimensional coverage index set includes dynamic coverage strength index, dynamic link quality index, multi-user concurrent performance index, and extreme environment adaptation index. S2. Perform communication coverage testing on the airborne base station. During the test, simultaneously collect the real-time flight positioning parameters of the airborne base station, the environmental parameters of the test scenario, and the communication coverage performance data corresponding to the four-dimensional coverage index set. S3. Based on the qualified threshold configured in step S1, perform compliance verification on the communication coverage performance data collected in S2, and output the test results of the airborne base station communication coverage performance.

[0032] The testing process of this invention uses a dynamic environment dual-adaptation four-dimensional coverage index system as the evaluation benchmark and adopts a lightweight testing architecture (i.e., a testing architecture with low power consumption, miniaturization, high adaptability, and adaptability to airborne dynamic scenarios) to perform a layered and progressive testing process on airborne emergency communication base stations. During the testing process, through the aforementioned lightweight testing architecture, all coverage performance parameters covered by the four-dimensional coverage index system are collected in real time. At the same time, in each test stage of the layered testing process, the flight parameters (including flight altitude, flight speed, flight attitude, etc.), positioning information (including latitude, longitude, altitude, etc.), and environmental parameters (including rainfall intensity, terrain type, smoke concentration, etc.) of the airborne base station are collected synchronously. The collected coverage performance data is compared with the preset performance qualification threshold to complete the index verification of the communication coverage performance of the airborne base station and provide data support for subsequent performance optimization.

[0033] The four-dimensional coverage indicator system includes dynamic coverage strength indicators, dynamic link quality indicators, multi-user concurrency performance indicators, and extreme environment adaptability indicators. This system provides a comprehensive and systematic basis for evaluating the communication coverage performance of airborne base stations. Specifically: the dynamic coverage strength indicator characterizes the signal coverage strength characteristics and dynamic adaptability of the airborne base station; the dynamic link quality indicator characterizes the stability and reliability of the signal transmission link; the multi-user concurrency performance indicator characterizes the communication service capability of the airborne base station in scenarios with multiple users accessing simultaneously; and the extreme environment adaptability indicator characterizes the operational adaptability and stability of the airborne base station in emergency extreme environments. These four indicators work together to form a complete coverage performance evaluation system, ensuring the core performance dimensions of emergency communication for tested airborne base stations.

[0034] The tiered testing process includes single-user dynamic testing, multi-user concurrent testing, extreme environment simulation testing, and scenario-based verification. The testing process follows a progressive testing logic of "from simple to complex, from basic to comprehensive," and the following tests are conducted sequentially: Single-user dynamic testing verifies the basic coverage performance of the airborne base station in a single-user access scenario; multi-user concurrent testing verifies the service capabilities of the airborne base station in a scenario where multiple users access the station simultaneously; extreme environment simulation testing verifies the adaptability of the airborne base station in emergency extreme environments (such as heavy rain, dense smoke, complex terrain, etc.); and scenario-based verification testing verifies the comprehensive coverage effect of the airborne base station in conjunction with actual emergency communication scenarios, ensuring that the test results align with actual application requirements.

[0035] Dynamic coverage strength indicators include time-weighted reference signal received power (RSRP) and interference-resistant reference signal received power (IRSRP) calculated with environmental compensation coefficient. Both indicators characterize the signal coverage strength and interference resistance of airborne base stations and are suitable for dynamic airborne flight scenarios. The time-weighted reference signal received power (RSRP) is calculated by weighting and summing the reference signal received power collected within a preset time period, eliminating the impact of instantaneous signal fluctuations on the test results and improving the accuracy of indicator calculation. The interference-resistant reference signal received power (IRSRP) is based on the time-weighted reference signal received power and introduces an environmental compensation coefficient to correct for signal attenuation caused by environmental interference, accurately characterizing the signal coverage strength and interference resistance of airborne base stations in complex environments.

[0036] Dynamic link quality indicators include the signal-to-interference-plus-noise ratio (SINR) calculated using a short-time window, the block error rate (BLER) calculated using continuous transmission blocks, and the penetration rate. These three indicators work together to characterize the stability, reliability, and penetration capability of the airborne base station signal transmission link. The SINR calculated using a short-time window is used to calculate the ratio of signal power to interference-plus-noise power in real time within the window, accurately capturing the instantaneous changes in link quality during the dynamic movement of the airborne base station. The BLER calculated using continuous transmission blocks characterizes the reliability of link transmission by calculating the proportion of erroneous data blocks in continuously transmitted data blocks; the lower the BLER, the stronger the link transmission stability. The penetration rate characterizes the ability of the airborne base station signal to penetrate obstacles (such as buildings, dense smoke, vegetation, etc.), directly affecting the effectiveness of signal coverage in emergency scenarios.

[0037] Multi-user concurrent performance metrics include regional user access success rate categorized by user density and handover interruption duration. These two metrics characterize the service quality and continuity of airborne base stations in multi-user concurrent access scenarios: regional user access success rate categorized by user density, which is determined by classifying user density within the test area and statistically analyzing the proportion of users successfully accessing the airborne base station at each density level to ensure stable access service under different user density scenarios; and handover interruption duration, which characterizes the interruption time when user terminals switch signals between different base stations or different beams during the movement of the airborne base station. The shorter this duration, the better the continuity of communication services in multi-user concurrent scenarios can be guaranteed, meeting the real-time requirements of emergency communication.

[0038] Extreme environment adaptability indicators include an environmental adaptability coefficient based on comprehensive multi-dimensional indicators and equipment calibration deviation. These two types of indicators characterize the operational adaptability and equipment stability of airborne base stations in emergency extreme environments: the environmental adaptability coefficient, calculated by weighting and summing the compliance rates of anti-interference reference signal received power, penetration rate, and block error rate statistically obtained from continuous transmission blocks under extreme environments, comprehensively evaluates the overall coverage performance of airborne base stations in extreme environments; the equipment calibration deviation characterizes the degree of deviation in the calibration accuracy of the airborne base station equipment itself under extreme environments. The smaller the deviation value, the stronger the operational stability of the airborne base station equipment under extreme environments, and the higher the accuracy of the test data.

[0039] The interference immunity reference signal received power is based on the time-weighted reference signal received power, superimposed with rainfall attenuation compensation, terrain obstruction compensation, and dense smoke attenuation compensation. The environmental compensation coefficients for each compensation item are configured according to the corresponding environmental parameters. The time-weighted reference signal received power is used as the basic calculation value, and three types of environmental attenuation compensation items are superimposed: rainfall attenuation compensation (to correct the attenuation effect of rainfall), terrain obstruction compensation (to correct the attenuation effect of terrain obstruction), and dense smoke attenuation compensation (to correct the attenuation effect of dense smoke). The environmental compensation coefficients for each environmental compensation item are configured according to the level of the corresponding environmental parameter (e.g., rainfall intensity is divided into three levels: light rain, moderate rain, and heavy rain, with different rainfall attenuation compensation coefficients configured accordingly), ensuring that the compensated interference immunity reference signal received power can accurately reflect the base station signal coverage strength in complex environments.

[0040] The environmental adaptability coefficient is obtained by weighting and summing the compliance rates of the anti-interference reference signal received power, penetration rate, and block error rate (calculated using continuous transmission blocks) with fixed weights. Doppler frequency shift compensation is introduced for the signal-to-interference-plus-noise ratio (SINR) calculated using a short time window. The environmental adaptability coefficient is obtained by assigning preset fixed weights to the compliance rates of the three core indicators (anti-interference reference signal received power compliance rate, penetration rate compliance rate, and block error rate compliance rate) and then weighting and summing them. The weight allocation can be preset according to the core needs of emergency communication to ensure the rationality of the comprehensive evaluation. The Doppler frequency shift compensation term is introduced for the signal-to-interference-plus-noise ratio (SINR) calculated using a short time window to correct the impact of Doppler frequency shift generated during the dynamic movement of the airborne base station on signal quality, improving the accuracy of SINR statistics and thus enhancing the reliability of link quality evaluation.

[0041] Single-user dynamic testing involves collecting dynamic coverage strength data at spatial sampling intervals and dynamic link quality data within time windows. Multi-user concurrent testing configures a hybrid service model comprising voice, video, and data services in a specified ratio. Extreme environment simulation testing calibrates the test equipment according to a preset environmental calibration coefficient mapping table. During single-user dynamic testing, dynamic coverage strength data is collected at preset spatial sampling intervals to ensure uniformity of coverage performance testing across spatial dimensions; dynamic link quality data is collected within preset time windows to ensure real-time changes in link quality under dynamic scenarios. During multi-user concurrent testing, a hybrid service model comprising voice, video, and data services in a preset ratio is configured to simulate the service needs of multiple users in actual emergency scenarios, ensuring test results closely match real-world applications. Before extreme environment simulation testing, the test equipment must be calibrated according to a preset environmental calibration coefficient mapping table, which corresponds to the relationship between different extreme environment parameters and calibration coefficients, ensuring the test accuracy of the equipment under extreme conditions and avoiding the impact of equipment errors on test results.

[0042] When comparing coverage performance data with preset thresholds, the 3σ criterion is used to remove outliers from the various coverage performance data under the four-dimensional coverage index system. That is, under the normal distribution, data that deviates from the mean by more than three times the standard deviation are removed. Outliers are mainly abnormal test data caused by factors such as equipment failure and sudden environmental changes. This avoids abnormal data from interfering with the index verification results and improves the reliability and rigor of the test conclusions.

[0043] If the performance indicators fail to meet the standards, the beam pointing, transmit power, or environmental compensation coefficient of the airborne base station is adjusted, and the test steps for the non-compliant items in the layered testing process are re-executed until the indicators meet the standards. This forms a closed-loop testing mechanism: If, after performance indicator verification, one or more coverage performance indicators of the airborne base station fail to reach the preset threshold, the key parameters of the airborne base station are adjusted. These adjusted parameters include beam pointing (to optimize signal coverage range and direction), transmit power (to adjust signal coverage strength), and environmental compensation coefficient (to optimize environmental interference correction accuracy). After parameter adjustment, it is not necessary to re-execute the entire layered testing process; only the test steps for the non-compliant indicators are re-executed. The above adjustment and retesting process is repeated until all coverage performance indicators reach the preset threshold, ensuring that the airborne base station meets emergency communication coverage requirements.

[0044] Furthermore, the beam pointing is adjusted in angular steps, and the transmit power is adjusted in power steps within a preset range. During beam pointing adjustment, it is gradually adjusted according to preset angular steps, which are preset based on the beam control accuracy and coverage requirements of the airborne base station to avoid excessive adjustment that could lead to unstable signal coverage. During transmit power adjustment, it is gradually adjusted within a preset power range, according to preset power steps, which are preset based on the hardware performance and emergency coverage requirements of the airborne base station. This ensures that the signal coverage strength meets the requirements while avoiding resource waste and signal interference caused by excessive transmit power.

[0045] Example 2 See Figure 9 An airborne base station communication coverage testing system for emergency communications, used to implement an airborne base station communication coverage testing method for emergency communications, comprising: The parameter configuration module is used to configure parameters that cover the performance evaluation benchmark. The test execution module is used to perform communication coverage tests on airborne base stations. The data acquisition module is used to synchronously collect real-time flight positioning parameters, environmental parameters, and communication coverage performance data during the test. The indicator verification module is used to verify the compliance of communication coverage performance data and output the test results.

[0046] It also includes a closed-loop optimization module, which is used to adjust the corresponding parameters of the airborne base station and trigger a retest when an indicator fails to meet the standard.

[0047] Example 3 A method for testing communication coverage of airborne base stations for emergency communication. As a highly mobile aerial device, drones are widely used in video shooting, post-disaster user positioning and communication, pesticide spraying in agriculture, border intrusion detection, and forest fire prevention. In these fields, given the dynamic deployment and superior communication link performance of drones, building drone flight and communication systems equipped with small base stations undoubtedly has broad prospects. Currently, the continuous development of 5G and 6G has placed more stringent requirements on the latency, bandwidth, and robustness of base station communication. During this period, drone base stations are developing rapidly as a supplementary component. Compared to ground base stations, drone base stations have a higher probability of line-of-sight transmission links and are more flexible in deployment. Focusing on the communication between drone base stations and ground users, a number of drone base station deployment and planning schemes have emerged based on different factors considered. The deployment methods of drones as aerial base stations are mainly divided into two categories: direct access and relay access. In the direct access mode, the drone, as an aerial communication node, connects directly to the ground core network through high-bandwidth backhaul links such as satellites, forming an aerial access point independent of ground infrastructure, such as... Figure 1 As shown. In relay access mode, drones act as relay nodes, forwarding signals between ground base stations and the core network, or collaborating with other high-altitude platforms, satellites, and other facilities to construct a multi-layered, integrated air-space-ground communication network. This improves coverage, system capacity, and network resilience, adapting to diverse application scenarios, such as... Figure 2 As shown in the figure. This embodiment proposes dynamic coverage evaluation indicators and efficient testing methods for drone base stations in direct access mode.

[0048] This embodiment addresses the dynamic operating characteristics of airborne base stations—"low altitude, high speed, and mobility"—and, in conjunction with the core requirement of adapting to extreme environments, establishes a four-dimensional dynamic coverage evaluation system. All indicators fully consider the propagation characteristics in the 500-5000 meter low-altitude domain, the 200-800 km / h high-speed mobile scenario, and the interference requirements in extreme environments.

[0049] Dynamic coverage intensity index: Time-averaged reference signal received power (RSRP-Time): Within a specified bandwidth of the LTE / 5G system, the time-weighted average power of the reference signal based on a 100ms sampling period. A weighting coefficient positively correlated with signal stability is used (0.8 weight for stable periods, 0.2 weight for fluctuating periods), effectively reducing instantaneous fluctuation interference. The measurement bandwidth is adapted to the 10-100MHz system frequency band, fully considering the propagation characteristics of low-altitude fuselage reflection and path loss varying with altitude. Based on 50m×50m spatial grid sampling, a four-level dynamic coverage area proportion evaluation standard is established, as shown in Table 1. Table 1. Level 4 Dynamic Coverage Assessment Table Coverage level RSRP-Time threshold area percentage supports business requirements High-quality coverage ≥-85dBm, ≥80% 4K video backhaul, real-time command and dispatch, and other high-speed services. Good coverage -95dBm > RSRP -Time ≥ -85dBm ≥ 15% for high-definition video communication requirements Basic coverage -105dBm > RSRP -Time ≥ -95dBm ≥ 5% Voice and data service guarantee Areas with weak coverage (<-105dBm <5%) require optimization. Anti-interference reference signal received power (RSRP-Anti): A signal strength indicator designed for extreme environments (heavy rain, dense smoke, mountainous terrain). It has a preset environment adaptation compensation coefficient and dynamically adjusts the path loss compensation value directly according to the scenario. The formula is: RSRP-Anti = RSRP-Time + α × Rainfall Attenuation Compensation + β × Terrain Obstruction Compensation + γ × Smoke Attenuation Compensation Wherein, α is the rainfall attenuation compensation coefficient (α=3dB when rainfall intensity >20mm / h, α=1.5dB when rainfall intensity is 5-20mm / h, and α=0.5dB when rainfall intensity is <5mm / h); β is the terrain shading compensation coefficient (β=2.5dB for mountainous terrain, β=1.5dB for hilly terrain, and β=0.3dB for plain terrain); and γ is the smoke attenuation compensation coefficient (γ=4dB when visibility is <300m, γ=2dB when visibility is 300-500m, and γ=0dB when visibility is >500m).

[0050] The threshold settings for this indicator are: ≥-95dBm in dense smoke environment, ≥-100dBm in rainstorm environment, and ≥-102dBm in mountain environment.

[0051] Dynamic link quality metrics: Dynamic Signal-to-Interference-plus-Noise Ratio (SINR-Dyn): In high-speed mobile scenarios, an instantaneous SINR statistical method with a 10ms window is used. A Doppler frequency shift compensation algorithm with fixed parameters is employed to accurately capture the effects of Doppler frequency shift and low-altitude multipath interference. Quality thresholds are set differently based on service requirements: voice services ≥5dB (QPSK modulation), high-speed data services ≥12dB (256QAM modulation), and voice services ≥3dB in extreme environments.

[0052] Dynamic Block Error Rate (BLER-Dyn): Based on a statistical mechanism of the error proportion of 100 consecutive transport blocks, it monitors link stability in real time during the movement of the airborne platform. By balancing random errors and signal hysteresis, it sets target values ​​of ≤2% for the control channel and ≤12% for the data channel (including 0.8dB HARQ gain), providing the system with a basis for millisecond-level link adaptive adjustment.

[0053] Signal Penetration Rate: Quantifies the effective penetration capability of a signal under extreme conditions. It is defined as "the ratio of the effective coverage area (RSRP-Anti≥threshold) to the physical coverage area", requiring ≥60% in forest scenarios, ≥50% in dense smoke scenarios, and ≥70% in rainstorm scenarios.

[0054] Multi-user concurrency performance metrics: Regional user access success rate: For multi-terminal concurrent scenarios such as emergency communication and low-altitude operations, the success rate is assessed in a tiered manner based on user density in the core coverage area. Density is defined by the number of users per square kilometer: ≥98% success rate at 80% user density (200 users per square kilometer), ≥99% at 50% user density (120 users per square kilometer), and ≥99.5% at 20% user density (50 users per square kilometer); in extreme environments (heavy rain / dense smoke), the success rate is ≥95% at 80% user density.

[0055] Handover interruption duration: Accurately calculate the service interruption time during handover between airborne and ground base stations, using a cumulative measurement method from link disconnection to re-establishment. Taking full account of the impact of antenna angle offset caused by changes in flight attitude, a target value of ≤30ms is set.

[0056] Extreme environment adaptability indicators: Environmental Adaptability Coefficient (EAC): This comprehensively evaluates the coverage stability of airborne base stations in extreme environments. The calculation formula is as follows: EAC = (RSRP - Anti compliance rate × 0.4) + (Penetration - Rate × 0.3) + (BLER - Dyn compliance rate × 0.3) Among them, RSRP-Anti compliance rate = number of test points that meet the threshold requirements / total number of test points; BLER-Dyn compliance rate = test periods that meet the error rate requirements / total test periods.

[0057] Target value: EAC ≥ 85% (heavy rain / dense smoke / mountainous environment).

[0058] Equipment calibration deviation (Calib-Error): The power measurement deviation of the test equipment under extreme environments. By using preset calibration rules based on environmental parameters (such as increasing the calibration value by 0.5dB for every 10°C decrease in temperature), the deviation is controlled within ±1dB to ensure the accuracy of test data.

[0059] This embodiment adopts a test architecture of "lightweight deployment, rapid data collection, and simple verification", focusing on the core requirements of airborne base stations such as "high-speed mobility, extreme adaptability, and emergency response". The test process is convenient to operate and highly feasible.

[0060] Core testing equipment: The system utilizes a combination of portable and highly adaptable equipment to ensure rapid deployment and accurate data collection. Core equipment includes: a drone-mounted test terminal supporting LTE / 5G multi-mode compatibility, suitable for high-speed mobile scenarios of 200-800 km / h, weighing ≤4kg for easy airborne deployment; a high-precision GPS / BeiDou dual-mode positioning module with an update frequency of 10Hz, positioning accuracy ≤1 meter, and simultaneous collection of flight altitude, speed, and other parameters; a portable spectrum analyzer adapted to 10-100MHz test bandwidth, supporting real-time collection of indicators such as RSRP and SINR, with a battery life ≥4 hours, meeting the needs of emergency field testing; a multi-user concurrent simulation terminal supporting flexible configuration of 1-200 users, capable of simulating mixed voice, video, and data services, with a deployment time ≤10 minutes; and an integrated environmental sensor that simultaneously collects temperature, rainfall intensity, and visibility data, providing a basis for environmental adaptability.

[0061] Before testing, the equipment must be quickly calibrated: the terminal power error should be calibrated to within ±1dB; through on-site calibration, the path loss compensation coefficient corresponding to the altitude of 500-5000 meters should be preset to eliminate the interference of the fuselage reflection; the environmental sensor and the test terminal should be synchronized in time (synchronization accuracy ≤1ms) to ensure the consistency of data in time and space.

[0062] Test process: 1. Single-user dynamic testing Adapted for high-speed scenarios of 200-800km / h, the process for quickly verifying dynamic coverage strength and link quality indicators is as follows: (1) Test preparation: Set the flight profile - the altitude is divided into 5 levels at 500m intervals: 500m, 1000m, 2000m, 3000m and 5000m; the speed is divided into 4 levels at 200km / h intervals: 200km / h, 400km / h, 600km / h and 800km / h.

[0063] (2) Data acquisition: The test platform flies according to the preset profile and collects one set of RSRP-Time data every 20 meters of space (weighted calculation based on a 100ms sampling period); collects one set of SINR-Dyn data every 10ms time window and enables the preset Doppler frequency shift compensation parameters; synchronously records flight parameters, positioning information and environmental data, and stores the data to the local terminal in real time.

[0064] (3) Data preprocessing: The 3σ criterion is used to remove outliers (such as signal mutations and location drift data) to ensure data integrity ≥99%; the data is sorted and organized according to the "height-speed" dimension to form a dynamic performance dataset.

[0065] (4) Indicator verification: Compare the test data with the preset threshold to determine whether the RSRP-Time coverage level ratio and SINR-Dyn compliance rate meet the requirements.

[0066] 2. Multi-user concurrent testing To adapt to the multi-user concurrent requirements of emergency scenarios, the process of tiered verification of access success rate and business continuity is as follows: (1) Test preparation: Set up 3 user density levels - 20% density (50 users / km²), 50% density (120 users / km²), and 80% density (200 users / km²); the multi-user simulation terminal is configured with a mixed service model with a ratio of 30% voice, 40% video, and 30% data, and the preset service duration is 10 minutes.

[0067] (2) Service initiation and data collection: Initiate services in sequence according to density level, and collect the regional user access success rate, RSRP-Time interval distribution, and BLER-Dyn value under each level; after the test of each density level is completed, adjust the base station transmission power (±3dB range) and enter the next level test.

[0068] (3) Indicator verification: Check whether the access success rate meets the standard under each density level, and whether BLER-Dyn meets the requirements of control channel ≤2% and data channel ≤12%.

[0069] 3. Extreme Environment Simulation Test The environmental adaptability indicators are verified by recreating extreme scenarios in a simulation chamber. The process is as follows: (1) Test preparation: Build an extreme environment simulation chamber and set the target scenario parameters - rainstorm scenario (temperature 10℃, rainfall intensity 20mm / h, visibility 300m), dense smoke scenario (temperature 25℃, visibility 200m, no rainfall), low temperature scenario (temperature -40℃, visibility 500m, no rainfall); the test equipment integrates environmental sensors and completes calibration according to the preset "environment-calibration coefficient" mapping table.

[0070] (2) Data acquisition: The test platform flew at an altitude of 2000m and a speed of 400km / h in the simulation cabin, and collected one set of RSRP-Anti, signal penetration rate and EAC data every 10 meters; environmental parameters and equipment calibration deviation were recorded simultaneously.

[0071] (3) Parameter optimization: If the indicators do not meet the standards (e.g., EAC < 85%), adjust the environmental compensation coefficient and retest and verify.

[0072] 4. Scenario-based verification testing The full-scenario performance verification was completed by combining static benchmarks and dynamic boundary tests. The process is as follows: (1) Static benchmark test: Ten fixed test points were set up on the ground at 100-meter intervals, and 30 minutes of static RSRP-Time and SINR-Dyn data were collected to establish performance benchmark values.

[0073] (2) Dynamic boundary test: Design a flight path (altitude 2000m, speed 400km / h) along the coverage boundary of the airborne base station beam, and collect BLER-Dyn, handover interruption duration and weak coverage area ratio data.

[0074] (3) Performance verification: Compare dynamic data with static benchmark values ​​to verify that the proportion of weak coverage area is <5%, the handover interruption time is ≤30ms, and the EAC is ≥85% in extreme environments; generate scenario-based verification reports to clarify the optimization direction (such as adjusting beam pointing in weak coverage areas and optimizing compensation coefficients in extreme environments).

[0075] Data processing and optimization: In the data processing stage, the collected data is classified according to "spatiotemporal tags," and a dynamic coverage trajectory map and an extreme environment impact distribution map are generated using a 50m×50m×5s three-dimensional grid. This allows for the intuitive identification of weak coverage areas and substandard scenarios. Subsequently, the optimization and adjustment stage is entered. For weak coverage areas, the beam pointing is adjusted in 0.2° steps, or the transmission power is increased in 1dB steps. For substandard scenarios under extreme environments, the corresponding compensation coefficients (α / β / γ) are optimized. Finally, closed-loop verification is performed, and the corresponding test process is repeated until the indicators meet the standards. The time for a single optimization iteration is ≤30 minutes, ensuring rapid implementation and effectiveness in emergency scenarios.

[0076] This embodiment addresses the "low-altitude, high-speed, and extreme environment" characteristics of airborne base stations by constructing a dynamic coverage indicator system and a dynamic-environment dual-adaptation four-dimensional coverage indicator system. This system covers dynamic coverage strength, dynamic link quality, multi-user concurrent performance, and extreme environment adaptation. Environmental adaptation is achieved through preset scenario-based compensation coefficients, solving the problem of inaccurate measurement of existing static indicators. An extreme environment testing scheme specifically designed for emergency scenarios of airborne base stations is presented. Through hardware integration and preset calibration rules, accurate testing under extreme conditions is achieved, solving the problem of insufficient extreme environment adaptation in existing testing methods. A "short-cycle, low-deployment-cost" testing process is constructed, eliminating the need for complex network topology and adapting to rapid post-disaster assessment within 4 hours, solving the problems of low efficiency and long cycles in existing testing methods.

[0077] Precisely matching the core requirements of airborne base stations for "low-altitude, high-speed, and extreme emergency response," this embodiment achieves comprehensive advantages in adaptability, efficiency, accuracy, and feasibility through targeted technical solution design. Specifically, compared to static evaluation schemes for ground-based fixed base stations, this embodiment overcomes the limitations of "static assumptions" and constructs a dynamic-environment dual-adaptive index system: high-speed fluctuation interference is reduced through RSRP-Time time-weighted calculation, and combined with RSRP-Anti's graded environmental compensation coefficient, the coverage estimation deviation in extreme environments is controlled within 5%, solving the "inaccuracy" problem in dynamic scenarios; lightweight test equipment deployment, with a single-process test ≤ 1 hour, adapts to emergency timeliness requirements. Compared to wide-area evaluation schemes for satellite communications, this embodiment significantly reduces deployment costs and time: a lightweight combination of a UAV-mounted terminal and a portable spectrum analyzer eliminates the need for several days of deployment preparation; the test resolution reaches 50m×50m, accurately capturing local coverage details, perfectly meeting the needs of rapid emergency evaluation. Compared to traditional emergency communication testing solutions, this embodiment achieves quantitative evaluation and extreme adaptability upgrades: It establishes a four-dimensional quantitative indicator system, adding core parameters such as handover interruption duration (≤30ms) and EAC (≥85%), solving the problems of "single indicators and insufficient quantification" in traditional solutions; it integrates environmental sensors and preset calibration rules, ensuring equipment error ≤±1dB, avoiding the environmental limitations of manual testing. Furthermore, the "measured data + preset rules" optimization mechanism of this embodiment requires no algorithm modeling, with a single iteration time ≤30 minutes, achieving efficient, low-cost, and practical airborne base station coverage evaluation, systematically solving the core problems of existing technologies such as "inaccurate measurement, low efficiency, high cost, and poor adaptability."

[0078] Furthermore, regarding the testing platform, drones can be replaced with tethered balloons or light helicopters, all of which can stably carry the testing terminal and synchronously collect flight parameters. Environmental sensors can be changed from integrated to a distributed network, achieving data synchronization through BeiDou time synchronization. The multi-user simulation terminal can replace dedicated hardware with an SDR software virtualization system, flexibly adapting to different user scales and business types. In terms of indicator weighting logic, fixed weights can be replaced with tiered weights triggered by fluctuation thresholds. The testing process can be changed from a serial to a "single-user + multi-user parallel" mode, significantly shortening the total cycle. The beam optimization step size can be adjusted from a fixed 0.2° step size to a tiered adjustment method of "initial 0.5° large step size + subsequent 0.1° fine step size". In extreme environment testing, the simulation cabin can be replaced with a solution of natural extreme scenarios + on-site calibration, coupled with distributed sensors to assist data collection, ensuring that the evaluation accuracy is not reduced.

[0079] Figure 1 Schematic diagram of direct access mode for drone base stations: This diagram illustrates the direct access architecture for drone base stations: Drones connect to the core network via satellite to directly serve mobile terminals. This is the core application scenario of this embodiment and the basis for evaluating the corresponding direct access mode.

[0080] Figure 2 Schematic diagram of drone base station relay access mode: This shows the relay access architecture: the drone connects to the ground base station and the core network, and the terminal accesses the network through the ground base station. This is an auxiliary deployment method.

[0081] Figure 3 Airborne communication coverage indicator block diagram: It presents an evaluation system with four dimensions of indicators and is a visual representation of the core technical solution.

[0082] Figure 4 Single-user dynamic testing flowchart: This diagram shows the dynamic testing process in a single-user scenario: starting from "start", the test preparation (setting the flight profile of altitude / speed) is executed in sequence, followed by data acquisition (acquiring RSRP-Time and SINR-Dyn), data preprocessing (removing outliers through the 3σ criterion), index verification (comparing with preset thresholds), and finally ending.

[0083] Figure 5 Multi-user concurrent testing flowchart: This diagram presents the concurrent testing process for multi-user scenarios: Starting with "Start", the test preparation is completed first, then the business initiation and data collection are performed (data is collected in stages according to density level and the transmission power is adjusted), and finally the indicator verification is performed (user access success rate and BLER data are checked), and the process ends.

[0084] Figure 6Extreme Environment Simulation Test Flowchart: This diagram shows the simulation test process under extreme conditions: starting from "Start", first complete the test preparation, then perform data acquisition, then perform parameter optimization (determine whether EAC is ≥85%, if not, adjust the compensation coefficient and retest), and the process ends after the target is met.

[0085] Figure 7 Scenario-based verification test flowchart: This diagram presents the test process for full-scenario verification: After "start", (static benchmark test) and dynamic boundary test are executed in parallel. Then, the performance verification stage (comparing dynamic data with static benchmark) is passed, and the process finally ends.

[0086] Many embodiments and applications beyond the examples provided will be apparent to those skilled in the art upon reading the foregoing description. Therefore, the scope of this teaching should not be determined by reference to the foregoing description, but rather by reference to the foregoing claims and the full scope of their equivalents. For purposes of completeness, all articles and references, including patent applications and publications, are incorporated herein by reference. The omission of any aspect of the subject matter disclosed herein in the foregoing claims is not intended as a waiver of that subject matter, nor should it be construed as an indication that the applicant has not considered that subject matter as part of the disclosed inventive subject matter.

[0087] The above content provides a further detailed description of the present invention. It should not be construed that the specific embodiments of the present invention are limited to this. For those skilled in the art, several simple deductions or substitutions can be made without departing from the concept of the present invention, and all such deductions or substitutions should be considered to fall within the scope of protection defined by the present invention.

Claims

1. A method for testing communication coverage of an airborne base station for emergency communication, characterized in that, Includes the following steps: S1. For the airborne base station to be tested, configure coverage performance evaluation benchmark parameters. The benchmark parameters include a four-dimensional coverage index set for dynamic environment dual adaptation, and the qualified threshold corresponding to each index. The four-dimensional coverage indicator set includes dynamic coverage strength indicators, dynamic link quality indicators, multi-user concurrency performance indicators, and extreme environment adaptation indicators. S2. Perform communication coverage test on the airborne base station. During the test, collect the real-time flight positioning parameters of the airborne base station, the environmental parameters of the test scenario, and the communication coverage performance data corresponding to the four-dimensional coverage index set. S3. Based on the qualified threshold configured in step S1, perform compliance verification on the communication coverage performance data collected in S2, and output the test results of the airborne base station communication coverage performance.

2. The airborne base station communication coverage testing method for emergency communication according to claim 1, characterized in that, In step S1, the dynamic coverage strength index includes time-averaged reference signal received power and interference immunity reference signal received power; The dynamic link quality indicators include dynamic signal-to-interference-plus-noise ratio, dynamic block error rate, and signal penetration rate. The multi-user concurrent performance indicators include regional user access success rate and handover interruption duration; the extreme environment adaptation indicators include environmental adaptability coefficient and equipment calibration deviation.

3. The airborne base station communication coverage testing method for emergency communication according to claim 2, characterized in that, In step S2, when collecting basic data on the anti-interference reference signal received power, environmental parameters such as rainfall intensity, terrain type, and dense smoke visibility are collected simultaneously to calculate the anti-interference reference signal received power with superimposed rainfall attenuation compensation, terrain occlusion compensation, and dense smoke attenuation compensation. When calculating the ratio of dynamic signal to interference plus noise, Doppler frequency shift compensation is introduced.

4. The airborne base station communication coverage testing method for emergency communication according to claim 1, characterized in that, In step S2, when performing communication coverage testing on the airborne base station, a progressive layered testing process is adopted, which sequentially performs single-user dynamic testing, multi-user concurrent testing, extreme environment simulation testing, and scenario-based verification testing. Corresponding parameters and communication coverage performance data are collected synchronously in each test stage.

5. The airborne base station communication coverage testing method for emergency communication according to claim 4, characterized in that, The single-user dynamic test includes a preset flight profile, which includes multiple flight altitude levels and flight speed levels, and controls the airborne base station to fly according to the preset flight profile. Data on dynamic coverage strength indicators are collected according to a preset spatial sampling interval, and data on dynamic link quality indicators are collected according to a preset time window. The multi-user concurrent test includes: presetting multiple user density levels, configuring a hybrid service model composed of voice, video, and data services in a preset ratio, initiating concurrent services sequentially according to the user density levels, and collecting corresponding communication coverage performance data.

6. The airborne base station communication coverage testing method for emergency communication according to claim 4, characterized in that, The extreme environment simulation test includes: first, setting extreme scenario parameters, calibrating the test equipment according to the preset environmental calibration coefficient mapping table, and then controlling the airborne base station to operate according to the preset flight profile and collect full index data. The scenario-based verification test includes first performing static benchmark tests to establish performance benchmark values, and then performing dynamic boundary tests to collect coverage continuity and switching performance data to complete full-scenario data collection.

7. The airborne base station communication coverage testing method for emergency communication according to claim 4, characterized in that, When the test results output in step S3 include items that fail to meet the standards, the beam pointing, transmit power, or corresponding environmental compensation coefficient of the airborne base station is adjusted, and the test steps corresponding to the items that fail to meet the standards are re-executed until all indicators meet the qualified threshold requirements, and the final test results are output; wherein, the beam pointing is adjusted according to a preset angle step size, and the transmit power is adjusted within a preset range according to a preset power step size.

8. The airborne base station communication coverage testing method for emergency communication according to claim 1, characterized in that, When performing compliance verification in step S3, the 3σ criterion is used to preprocess the communication coverage performance data collected in S2 to remove outliers.

9. An airborne base station communication coverage testing system for emergency communication, characterized in that, The method for testing the communication coverage of an airborne base station for emergency communication as described in any one of claims 1-8 includes a parameter configuration module for configuring coverage performance evaluation benchmark parameters. The test execution module is used to perform communication coverage tests on airborne base stations. The data acquisition module is used to synchronously collect real-time flight positioning parameters, environmental parameters, and communication coverage performance data during the test. The indicator verification module is used to verify the compliance of communication coverage performance data and output the test results.

10. The airborne base station communication coverage testing system for emergency communication according to claim 9, characterized in that, It also includes a closed-loop optimization module, which is used to adjust the corresponding parameters of the airborne base station and trigger a retest when an indicator fails to meet the standard.

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