5G three-dimensional coverage and capacity planning design method for low-altitude economy

Abstract

The invention relates to the field of low-altitude communication network planning methods, in particular to a 5G three-dimensional coverage and capacity planning design method for low-altitude economy, which comprises the following steps: performing airspace range limitation and application scene division on a target airspace, establishing a mobile model of a low-altitude terminal, and providing dynamic input for simulation; the method comprises the following steps: establishing a dual-frequency heterogeneous network, and determining base station addresses covering targets at different heights and meeting different signal station spacing; performing three-dimensional coverage and quality simulation on the established dual-frequency heterogeneous network, performing network KPI evaluation on the simulation until the standard is reached, and outputting a network deployment planning scheme; deploying according to a network deployment planning scheme, predicting low-altitude service flow, and adjusting a beam direction and a PRB reservation ratio to realize on-demand allocation of resources; and carrying out actual measurement on the deployed network, collecting an air measurement index, comparing a comparison deviation between the air measurement index and a simulation result, and carrying out fine adjustment on the network according to the comparison deviation. According to the invention, diversified communication requirements are met, and the success rate of terminal access is improved.

Description

Technical Field

[0001] This invention relates to the field of low-altitude communication network planning methods, specifically to a 5G three-dimensional coverage and capacity planning design method for the low-altitude economy. Background Technology

[0002] With the rapid development of the low-altitude economy, the number of low-altitude terminals such as UAVs and electric vertical take-off and landing (eVTOL) aircraft is growing at an annual rate of over 50%. Their communication needs exhibit three core characteristics: First, the terminals can move in three dimensions, with an altitude range of 0-300 meters and a speed of 0-300 km / h, which traditional 2D ground coverage cannot accommodate. Second, services are diversified, with beyond-line-of-sight control requiring ultra-low latency and ultra-high reliability, FPV image transmission requiring high speed (10-100 Mbps), and data backhaul requiring large bandwidth. Third, dense networking, with a terminal density of up to 500 units per square kilometer in a single airspace, requires extremely high capacity flexibility.

[0003] Existing terrestrial 5G networks have significant shortcomings in low-altitude scenarios: First, severe "tower-based blackouts" occur, with base station antennas tilting downwards, resulting in signal coverage blind spots exceeding 30% in the 0-50 meter low-altitude region. Second, interference is rampant, with uplink signals from terrestrial base stations interfering with downlink signals from low-altitude terminals, and areas with SINR below -5dB accounting for over 25%. Third, insufficient capacity flexibility, with no resources reserved for low-altitude services, resulting in a low-altitude terminal access success rate below 70% under high ground load. Fourth, propagation model mismatch occurs, with the traditional 3GPPUMi / UMa model failing to consider the "line-of-sight advantage" and "transition zone loss" in low-altitude environments, leading to simulation errors exceeding 15%.

[0004] Existing planning schemes mostly follow the ground network approach and have not built a three-dimensional planning system adapted to the characteristics of low altitude, making it difficult to meet the economic communication needs of low altitude. Summary of the Invention

[0005] The present invention aims to provide a 5G three-dimensional coverage and capacity planning design method for the low-altitude economy, so as to solve the problem that the communication needs of the low-altitude economy cannot be met.

[0006] The 5G three-dimensional coverage and capacity planning design method for the low-altitude economy in this solution includes the following steps: Step 1: Define the airspace range and application scenario for the target airspace. Based on historical flight trajectories, establish a motion model of the altitude change rate and turning frequency of the low-altitude terminal to provide dynamic input for simulation. Step 2: Establish a dual-frequency heterogeneous network with single base station coverage and single base station capacity, and determine the base station addresses that cover targets at different heights and meet different signal downstation spacing requirements; Step 3: Perform three-dimensional coverage and quality simulation on the established dual-frequency heterogeneous network, output coverage indicators, quality indicators and coverage blind spots, evaluate network KPIs through Monte Carlo service simulation, iteratively optimize based on coverage blind spots and KPI status until all KPIs are met, and output network deployment planning scheme. Step 4: Deploy according to the network deployment plan, predict low-altitude service traffic within a preset time period based on the LSTM model, and adjust the beam direction and PRB reservation ratio according to the prediction results to achieve on-demand resource allocation. Step 5: Perform actual tests on the deployed network, collect test metrics, and compare the test metrics with the simulation results from Step 3. Fine-tune the network based on the comparison deviation.

[0007] Preferably, in order to make the deployed network more in line with actual needs and the application scenarios more complete, in step 1, the airspace range includes the latitude and longitude boundaries of the planned area, the target altitude layer, the no-fly zone and the restricted flight zone. The target altitude layer includes the low-altitude area of ​​0-50m, the medium-low altitude area of ​​50-120m, and the medium-high altitude area of ​​120-300m. The application scenarios include logistics and distribution routes, eVTOL take-off and landing sites, and emergency rescue airspace.

[0008] Preferably, in order to reduce network coverage blind spots and eliminate signal dead zones, in step 2, the dual-frequency heterogeneous network is equipped with a distributed antenna system (DAS) and micro-stations.

[0009] Preferably, in order to provide signal coverage and avoid dead zones under signal towers, in step 2, the downtilt angle of the base station antenna is adjusted according to different spatial heights, and 3D beamforming is performed according to different spatial heights, dynamically switching the beam type based on the terminal height and position.

[0010] Preferably, in order to fully allocate network resources and improve network resource utilization, in step 2, different carriers are allocated according to different network services to plan frequencies, and low-altitude dedicated PRB pool resources are reserved in the base station scheduler. The reservation ratio is dynamically adjusted according to the service density.

[0011] Preferably, in order to ensure the smooth operation of various network services and optimize the utilization of network resources, in step 2, three types of end-to-end network slices are constructed according to different network services, including control slices, image transmission slices, backhaul slices, and slice isolation.

[0012] Preferably, in order to make the network suitable for different network services and improve the utilization of network resources, in step 3, during iterative optimization, if the coverage blind spot is >1%, adjust the base station position or antenna tilt angle; if the latency in the KPI does not meet the standard, increase the resource reservation ratio; if the interference is too high, optimize the beamwidth or frequency spacing; the number of iterations is ≥3 rounds until all KPIs meet the standard.

[0013] Preferably, in order to ensure the effectiveness of network adjustment and to prevent network anomalies caused by excessive adjustment, in step 5, if the comparison deviation is >5%, the fine-tuning process is to fine-tune the antenna tilt angle ±1° or the power ±1dBm.

[0014] Compared with existing technologies, this solution constructs a three-dimensional planning system adapted to low-altitude characteristics, performs dynamic resource optimization, and provides a precise and efficient 5G three-dimensional coverage and capacity planning scheme, which can meet the diverse communication needs of the low-altitude economy and improve the success rate of terminal access. Attached Figure Description

[0015] Figure 1 This is a schematic block diagram illustrating an embodiment of the 5G three-dimensional coverage and capacity planning design method for low-altitude economy of the present invention. Figure 2 This is a diagram of a dual-frequency heterogeneous network architecture for an embodiment of the 5G three-dimensional coverage and capacity planning design method for low-altitude economy of the present invention. Figure 3 This is a three-dimensional beam coverage comparison diagram of an embodiment of the 5G three-dimensional coverage and capacity planning design method for low-altitude economy of the present invention. Detailed Implementation

[0016] The following detailed description provides further details on specific implementation methods.

[0017] A 5G three-dimensional coverage and capacity planning design method for the low-altitude economy, such as Figure 1 As shown, it includes the following steps: Step 1 involves defining the airspace range and application scenario for the target airspace. Based on historical flight trajectories, a motion model for the altitude change rate and turning frequency of the low-altitude terminal is established to provide dynamic input for simulation. The motion model is dynamically adjusted according to the actual scenario. For example, the motion model is set to have an altitude change rate in the range of 0-5 m / s and a turning frequency in the range of 0-2 times / min. Simulation software used includes OPNET, MATLAB, and UAVNetSim. The dynamic adjustment of the motion model according to the actual scenario is due to two factors: firstly, the different physical performances of multi-rotor UAVs, eVTOLs, and fixed-wing UAVs result in corresponding adaptations for altitude change rate and turning frequency; secondly, the application scenario affects the parameters, which will fluctuate with operational requirements in scenarios such as emergency rescue (requiring rapid altitude increase and frequent turning), logistics delivery (uniform speed cruise with few turns), and eVTOL take-off and landing (vertical take-off and landing with no turning). Finally, the model needs to be statistically calibrated based on historical flight trajectory data of the target airspace to optimize the general range of the motion model to a precise range that fits reality, avoiding deviations between the model and the actual motion state and ensuring the accuracy of subsequent simulations.

[0018] The airspace scope includes the latitude and longitude boundaries of the planned area, target altitude layers, no-fly zones and restricted-fly zones. The target altitude layers include the low-altitude area of ​​0-50m, the medium-low altitude area of ​​50-120m, and the medium-high altitude area of ​​120-300m.

[0019] Scene segmentation: Based on building density and interference sources, the scenarios are divided into five categories: urban, suburban, rural, coastal, and airport periphery. Information on building density, interference sources, and line-of-sight ratio is collected for these five scenarios. Application scenarios include logistics and distribution routes, eVTOL take-off and landing sites, and emergency rescue airspace, and business hotspot areas are marked.

[0020] Terminals for the low-altitude economy include multi-rotor UAVs, fixed-wing UAVs, and eVTOLs. The data collection includes the proportion of terminals and flight parameters, such as multi-rotor speeds of 0-50 km / h and eVTOL speeds of 0-300 km / h.

[0021] The QoS requirements for network services are shown in Table 1.

[0022] Table 1 QoS Service Requirements

[0023] The Low Altitude City Model (AUMi) and the Close-to-Line-of-Sight (LoS) model from 3GPP TR 38.811 / 38.901 are adopted as the low-altitude propagation model. The model formula is expressed as follows: ; Where d is the propagation distance in km, f is the frequency in GHz, α(h) is the height correction factor, h is the terminal height, and h ranges from 0 to 300 m, and σ is the standard deviation of shadow fading.

[0024] Aerial calibration of the low-altitude propagation model: Flight tests were conducted using a drone carrying a 5G test terminal, which supports Sub-6GHz / millimeter wave. Test points were set up as follows: 20-30 test points were selected in each scenario, covering altitudes from 0 to 300 meters. Data acquisition was performed using a transmitter (base station) at a fixed power (43dBm) to collect RSRP and SINR data at each test point. Parameter optimization involved fitting α(h) using the least squares method and correcting σ to ensure the model error was ≤5%.

[0025] Step 2: Establish a dual-band heterogeneous network with varying coverage and capacity per base station, such as... Figure 2 As shown, base station addresses are determined to cover targets at different altitudes and meet different signal spacing requirements.

[0026] The antenna planning revolves around a dual-band heterogeneous network, which includes a coverage layer, a capacity layer, and a supplementary layer to meet the three-dimensional coverage requirements of low-altitude 0-300m: The coverage layer uses the Sub-6GHz band, configured with a 64-antenna array to generate a fan-shaped beam with a horizontal angle of 30° and a vertical angle of 20°, with an antenna downtilt angle of -3° to -8°, a station spacing of 800-1200m, covering the mid-to-high altitude domain of 120-300m and achieving 30dB+ sidelobe suppression; The capacity layer uses the millimeter-wave band, with a 64-antenna array to generate a point beam with a horizontal / vertical angle of 10°, an antenna downtilt angle of -8° to -15° (large negative tilt), a station spacing of 200-400m, covering low-altitude hotspots of 0-120m and eliminating "tower blackout"; The supplementary layer fills blind spots such as inside buildings and underground take-off and landing fields through a distributed antenna system (DAS) and micro-stations.

[0027] The dual-frequency heterogeneous network structure consists of a cover layer plus a capacity layer, combined with a supplementary layer, specifically: Coverage layer (Sub-6GHz, such as 3.5GHz): Single base station coverage radius of 500-800m, covering 120-300m of mid-to-high airspace, providing wide coverage and mobility management, with a single cell capacity of 1.5Gbps.

[0028] Capacity layer (millimeter wave, such as 28GHz): Single base station coverage radius of 100-300m, covering low-altitude hotspots (take-off and landing fields, flight routes) of 0-120m, providing ultra-high capacity, with a single cell capacity of 5Gbps.

[0029] The dual-band heterogeneous network is equipped with a distributed antenna system (DAS) and micro-stations, i.e., a supplementary layer, to cover blind spots such as inside buildings and underground take-off and landing fields, eliminating signal dead zones.

[0030] Network site selection: Prioritize the reuse of existing street light poles with a height of 8-12m, monitoring poles with a height of 10-15m, and the exterior walls of high-rise buildings with a height of 20-50m to reduce construction costs; the spacing between sites is: 800-1200m between Sub-6GHz base stations and 200-400m between millimeter-wave base stations to ensure continuous coverage.

[0031] Base station antenna tilt angle optimization involves adjusting the downtilt angle of the base station antenna according to different spatial altitudes. For example, for mid-to-high altitude coverage requirements, the downtilt angle of the Sub-6GHz base station antenna is adjusted to -3 to -8° (uptilt), with the main lobe pointing to the 120-300m airspace; for low-altitude coverage requirements, the downtilt angle of the millimeter-wave base station antenna is adjusted to -8 to -15°, with the main lobe pointing to the 0-120m airspace, solving the "tower blackout" problem; 3D beamforming is performed according to different spatial altitudes, such as... Figure 3 As shown, specifically, Massive MIMO (64-antenna array) is used to generate directional beams: a "fan-shaped beam" (30° horizontal beamwidth, 20° vertical beamwidth) is used at mid-to-high altitudes, and a "spot beam" (10° horizontal / vertical beamwidth) is used at low altitudes. Sidelobe suppression is achieved through digital beamforming technology, increasing the sidelobe suppression ratio to over 30dB, reducing interference to ground cells and adjacent airspace. The beam switching strategy dynamically switches beam types based on terminal altitude and location, with a switching delay of <20ms. For example, when the terminal descends from 150m to 50m, it switches from a fan-shaped beam to a spot beam. The method for dynamically switching beam types is as follows: the terminal reports altitude, position, and speed via the Uu interface at 10ms intervals, and the base station simultaneously and actively measures signal quality such as RSRP and SINR. The decision-making process for dynamically switching beam types is based on preset rules, which are: fixed matching point beams for altitudes of 0-120m, fixed matching fan-shaped beams for altitudes of 120-300m, wide beams for speeds >50km / h, and narrow beams for speeds ≤50km / h. When the signal quality drops below RSRP <-115dBm or SINR <-5dB, a backup beam is switched. During the actual execution phase, the base station directly calls the pre-stored beam weight parameters and adjusts them through Massive MIMO traditional digital beamforming.

[0032] Different carriers are allocated to plan frequencies based on different network services, and low-altitude dedicated PRB pool resources are reserved in the base station scheduler. The reservation ratio is dynamically adjusted according to service density to ensure that the access success rate of low-altitude terminals is ≥95% when the ground load is high (i.e., load >80%). The reservation rule method for dynamically adjusting the reservation ratio is as follows: First, dedicated carriers are allocated based on network service type (e.g., beyond-line-of-sight control services use dedicated Sub-6GHz carriers, FPV image transmission and data backhaul share millimeter-wave carriers), and an independent PRB pool is defined in the base station scheduler for the corresponding carrier. The reservation ratio is dynamically adjusted according to the real-time low-altitude service density: for example, during peak logistics and delivery periods and busy eVTOL take-off and landing periods, the reservation ratio is increased to 30%-40%, and decreased to 10%-15% during off-peak periods. At the same time, the ground load threshold is anchored (when the ground load is >80%) to forcibly ensure that the PRB pool resources are not crowded out by ground services, and to prioritize the reservation needs of high-priority services (such as emergency rescue and beyond-line-of-sight control), ultimately ensuring that the access success rate of low-altitude terminals is stable at ≥95%.

[0033] The frequency planning is as follows: Dedicated carrier planning: A dedicated Sub-6GHz carrier is allocated for beyond-line-of-sight control services; Shared carrier planning: FPV and data backhaul services share millimeter-wave carriers, distinguished by scheduling priority, with FPV having higher priority than data backhaul.

[0034] Three types of end-to-end network slices are constructed based on different network services: control slices, image transmission slices, backhaul slices, and slice isolation. Control slices use dedicated PRB resources, with latency <50ms, reliability 99.999%, and are suitable for beyond-line-of-sight control. Image transmission slices guarantee downlink bandwidth, with a rate of 10-100Mbps, latency <100ms, and are suitable for FPV. Backhaul slices use flexible bandwidth allocation, with a rate ≥50Mbps, and are suitable for data backhaul. Slice isolation: interference isolation between slices is achieved through hard slicing technology, and the QoS guarantee rate within a slice is ≥98%.

[0035] Step 3: Perform 3D coverage and quality simulation on the established dual-frequency heterogeneous network, outputting coverage indicators, quality indicators, and coverage blind spots. The simulation tool used is professional software supporting 3D modeling (WinProp, Remcom WirelessInSite). Import a 3D digital map of the planning area. During simulation, input the low-altitude propagation model from Step 1, the base station parameters from Step 2, and the antenna and beam parameters from Step 2. The latitude, longitude, altitude, and power settings of the base station parameters are differentiated based on the location of the dual-frequency heterogeneous network (coverage layer / capacity layer / supplementary layer): In terms of latitude and longitude, the coverage layer (Sub-6GHz) reuses 8-50m high streetlight poles / monitoring poles / building exteriors, with a station spacing of 800-1200m, avoiding interference sources, ensuring wide coverage in the mid-to-high altitude range of 120-300m; the capacity layer (millimeter wave) focuses on low-altitude hotspots, reuses matching poles, and has a station spacing of 200-400m; the supplementary layer (DAS / micro-stations) is deployed according to the blind spot locations, with latitude and longitude aligned with GIS to ensure accuracy. In terms of altitude, the cover layer is 8-50m, suitable for negative tilt angles of -3° to -8° pointing towards mid-to-high altitudes; the capacity layer is 10-15m, suitable for large negative tilt angles of -8° to -15° covering low altitudes; and the supplementary layer is 2-3m indoors and 3-5m outdoors, suitable for blind spot environments. In terms of power, the cover layer is 43-48dBm, adjusted according to building density; the capacity layer is 38-43dBm, taking the upper limit at hotspots; the supplementary layer is 15-20dBm for DAS and 20-25dBm for microstations; simulation height layers are set (50m, 100m, 150m, 200m, 300m), with 1000+ test points generated for each height layer. The simulation outputs the following indicators: coverage indicator is the coverage rate of each altitude layer with RSRP ≥ -110dBm (target ≥ 99%); quality indicator is the proportion of each altitude layer with SINR ≥ 3dB (target ≥ 95%); blind zone analysis is to mark coverage blind zones (RSRP < -110dBm), supplement micro base stations or adjust antenna parameters.

[0036] Network KPIs are evaluated using Monte Carlo simulation. Iterative optimization is performed based on coverage blind spots and KPI performance until all KPIs are met, resulting in a network deployment plan. The service load during simulation is as follows: 1000-5000 low-altitude terminals are simulated, distributed according to the service model in Table 1 (control: image transmission: backhaul = 1:3:2), and move randomly (conforming to the mobility model in step 1).

[0037] KPI evaluation includes the following indicators: access success rate (target ≥ 98%), throughput (FPV ≥ 10Mbps, backhaul ≥ 50Mbps); latency (control services < 50ms, image transmission services < 100ms), and disconnection rate (target < 0.1%).

[0038] During iterative optimization, when the coverage blind zone is >1%, the antenna tilt angle is adjusted precisely based on the location of the blind zone: if the blind zone is below the base station, the downtilt angle of the Sub-6GHz base station antenna is slightly adjusted upwards by 1°-2°, and the downtilt angle of the millimeter-wave base station antenna is slightly adjusted upwards by 2°-3°. If the blind zone is to the side of the base station (mid-to-high altitude), the antenna azimuth angle is slightly adjusted in the direction of the blind zone by 1°-3°. The adjustment of the antenna tilt angle is combined with the location of the blind zone and the base station, which can accurately adjust the antenna tilt angle while avoiding excessive adjustment that could create new blind zones. When the KPI latency is not met, the resource reservation ratio is increased according to the degree of latency deviation. For minor non-compliance with latency exceeding the target by 10%-20%, the reserved proportion of the low-altitude dedicated PRB pool will be increased by 5%-10%. For severe non-compliance with latency exceeding the target by more than 20%, the reserved proportion of the low-altitude dedicated PRB pool will be increased by 10%-15%, and the upper limit of the reserved proportion shall not exceed 40% to prevent resource waste. When interference is too high, optimize beamwidth or frequency spacing: when co-channel interference is the main issue, reduce the width of the mid-to-high altitude fan beam by 5°-10° and the width of the low-altitude point beam by 2°-5°. When adjacent channel interference is the main issue, increase the frequency spacing between adjacent base stations by 10%-20%. After each round of adjustment, re-simulate and evaluate, iterating for ≥3 rounds until all KPIs are met.

[0039] The output network deployment plan includes: Base station deployment table: including latitude and longitude, altitude, antenna type, azimuth, downtilt angle (including negative values), power, and frequency; Beam configuration table: Beam type, coverage height, and beam width for each base station; Resource allocation table: PRB reservation ratio, slice resource allocation, frequency planning; Construction specifications: Base station installation requirements, cable routing, and lightning protection measures.

[0040] Step 4: Deploy according to the network deployment plan. Predict low-altitude service traffic within a preset time period using the LSTM model, and adjust the beam direction and PRB reservation ratio based on the prediction results to achieve on-demand resource allocation. The preset time period is 15 minutes, and the reservation ratio is ±5%. Taking the urban low-altitude core area from 7:00 to 7:15 in the morning (15-minute prediction period) as an example: The LSTM model predicts in advance the terminal density of eVTOL take-off and landing sites and the significant increase in traffic on the eastern logistics routes during this period, as well as the increased proportion of beyond-line-of-sight control services; in terms of beam adjustment, millimeter-wave base stations around the take-off and landing sites will focus their beams on the core area (0-50m) and tilt them towards the eastern routes, while Sub-6GHz base stations will increase the beam gain of these routes; PRB reservation is based on 20%, with a 5% to 25% increase in hotspot areas (take-off and landing sites) to ensure low latency, and a 5% to 15% decrease in non-hotspot areas to release resources; after 15 minutes, as traffic decreases, the PRB ratio and beam direction are adjusted back to achieve on-demand allocation that ensures demand during peak hours and avoids waste during off-peak hours.

[0041] SON Function Deployment: Enable the base station self-organizing network function, including: Mobile Robustness Optimization (MRO): Dynamically adjusts the handover threshold based on the terminal's movement trajectory, achieving a handover success rate of ≥99.5%; Load balancing (MLB): In areas with high density of low-altitude terminals (>300 units / k) It automatically switches some terminals to neighboring cells to balance the load (single cell load <70%).

[0042] Step 5: Conduct on-site testing of the deployed network. Engineering deployment: Install base stations, antennas, and supporting equipment according to the plan outlined in Step 3, ensuring base station synchronization accuracy <1μs. Aerial testing verification uses a drone carrying a test terminal, covering all altitude layers of the planned airspace. Collect aerial test metrics, including RSRP, SINR, latency, and data rate, and compare the deviation between the aerial test metrics and the simulation results from Step 3. Fine-tune the network based on the deviation. If the deviation >5%, the fine-tuning process involves adjusting the antenna tilt angle by ±1° or the power by ±1dBm. Service verification: Simulate actual low-altitude services and conduct continuous testing for 24 hours to ensure KPIs are consistently met.

[0043] This embodiment's solution quantifies path loss and shadow fading characteristics in different scenarios by using an aerial measurement to correct the low-altitude propagation model (employing the 3GPP AUMi model). It employs a dual-band heterogeneous network of "Sub-6GHz + millimeter wave" (Sub-6GHz covering mid-to-high altitudes of 120-300 meters, millimeter wave covering low-altitude hotspots of 0-120 meters), combined with negative tilt antennas and 3D beamforming technology to generate directional fan-shaped or spot beams, solving the "tower blackout" problem. Furthermore, it allocates differentiated resources for services with different QoS requirements through air interface resource reservation (dedicated PRB pool) and network slicing technology. Finally, based on 3D simulation and AI dynamic optimization, it achieves coordinated optimization of coverage, capacity, and interference. This improves the target low-altitude coverage and communication quality, effectively providing highly reliable and resilient 5G communication support for the low-altitude economy. Dual-band networking and 3D beamforming can improve the coverage of the target low-altitude airspace (0-300m) with RSRP ≥ -110dBm. 3D beamforming achieves a sidelobe suppression ratio of over 30dB, eliminating "tower blackout" areas. Dual-band heterogeneous networking increases the single-airspace capacity to 6.5Gbps, and dynamic resource reservation and AI scheduling enable elastic capacity adjustment, improving terminal access success rate. Service QoS guarantees and network slicing provide differentiated guarantees for different services, reducing beyond-line-of-sight control latency, improving reliability and FPV rate compliance, meeting the diversified needs of the low-altitude economy, and solving technical challenges such as coverage blind spots, interference clutter, and insufficient capacity elasticity caused by terminal 3D movement and diversified services (beyond-line-of-sight control, FPV image transmission, autonomous navigation) in low-altitude scenarios (0-300m airspace).

[0044] The above descriptions are merely embodiments of the present invention, and common knowledge regarding specific structures and characteristics is not elaborated upon here. It should be noted that those skilled in the art can make various modifications and improvements without departing from the structure of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A method for 5G stereoscopic coverage and capacity planning design for low-altitude economy, characterized in that, The method comprises the following steps: Step 1: airspace range definition and application scenario division are performed for a target airspace, a moving model of height change rate and turning frequency of a low-altitude terminal is established based on historical flight trajectories, and dynamic input is provided for simulation; Step 2: a dual-frequency heterogeneous network of single-base station coverage range and single-base station capacity is established, base station addresses that cover targets at different altitudes and meet different signal inter-station distances are determined; Step 3: three-dimensional coverage and quality simulation is performed on the established dual-frequency heterogeneous network, coverage indicators, quality indicators and coverage blind areas are output, network KPI evaluation is performed through Monte Carlo service simulation, and iterative optimization is performed according to the coverage blind area and KPI conditions until all KPIs meet the standards, and a network deployment planning scheme is output; Step 4: deployment is performed according to the network deployment planning scheme, low-altitude service traffic in a future preset time period is predicted based on an LSTM model, and beam direction and PRB reservation ratio are adjusted according to the prediction result to realize on-demand allocation of resources; Step 5: measurement is performed on the deployed network, air measurement indicators are collected, and a comparison deviation between the air measurement indicators and the simulation results of step 3 is compared, and the network is fine-tuned according to the comparison deviation.

2. The 5G three-dimensional coverage and capacity planning design method for low-altitude economy according to claim 1, characterized in that: In step 1, the airspace range includes planning area latitude and longitude boundaries, target height stratification, no-fly zones and restricted flight zones, the target height stratification includes a low-altitude region of 0-50m, a medium-low altitude region of 50-120m, and a medium-high altitude region of 120-300m, and the application scenarios include logistics distribution routes, eVTOL take-off and landing fields, and emergency rescue airspaces.

3. The 5G three-dimensional coverage and capacity planning design method for low-altitude economy according to claim 1, characterized in that: In step 2, the dual-frequency heterogeneous network is provided with a distributed antenna system (DAS) and a micro station.

4. The 5G three-dimensional coverage and capacity planning design method for low-altitude economy according to claim 3, characterized in that: In step 2, the downtilt angle of the base station antenna is adjusted according to different spatial altitudes, and 3D beamforming is performed according to different spatial altitudes, and the beam type is dynamically switched based on the terminal height and position.

5. The 5G stereoscopic coverage and capacity planning design method for low-altitude economy according to claim 4, characterized in that: In step 2, different carriers are allocated according to different network services to plan the frequency, and low-altitude dedicated PRB pool resources are reserved in the base station scheduler, and the reservation ratio is dynamically adjusted according to the service density.

6. The 5G stereoscopic coverage and capacity planning design method for low-altitude economy according to claim 5, characterized in that: In step 2, three types of end-to-end network slices are constructed according to different network services, including control slices, image transmission slices, and backhaul slices, and slice isolation.

7. The 5G three-dimensional coverage and capacity planning design method for low-altitude economy according to claim 1, characterized in that: In step 3, during iterative optimization, if the coverage blind area is greater than 1%, the base station position or antenna tilt angle is adjusted; if the delay in the KPI does not meet the standards, the resource reservation ratio is increased; if the interference is too high, the beam width or frequency interval is optimized; the iteration is performed for 3 rounds or more until all KPIs meet the standards.

8. The 5G stereoscopic coverage and capacity planning design method for low-altitude economy according to claim 1, characterized in that: In step 5, if the comparison deviation is greater than 5%, the fine-tuning process is to fine-tune the antenna tilt angle by ±1° or fine-tune the power by ±1dBm.

Images