5G AeroMACS system base station site selection method

Abstract

The invention relates to the technical field of wireless communication, provides a 5G AeroMACS system base station site selection method, and considers the base station site selection problem from three aspects of base station deployment planning, frequency spectrum planning and network optimization. In the planning stage, the optimal position of the 5G base station can be scientifically determined, parameters such as the station spacing, the antenna hanging height and the antenna model are optimally configured, and the coverage effect is evaluated. The invention abandons the traditional method of constructing the base station only by experience, and ensures that the base station can effectively perform spectrum allocation and interference control. In an airport scene high flow and complex environment, wireless resources can be efficiently utilized, and the network operation efficiency and the user experience are improved.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and in particular to a 5G AeroMACS system base station site selection method. Background Art

[0002] 5G technology is a key new technology that currently supports the high-quality development of the civil aviation industry. In the field of civil aviation, there is an urgent need to combine 5G technology with existing aviation mobile communications, deeply integrate and apply 5G technology to enable smart civil aviation, promote the safe and high-quality development of civil aviation, and create a new era image for the civil aviation industry. In addition, as a new broadband communication technology included in the "China Civil Aviation New Generation Aviation Broadband Communication Technology Roadmap", AeroMACS is an aviation broadband mobile communication system for airport surface areas. It can provide broadband wireless network connections for airport surfaces, communicate with aircraft, emergency vehicles, baggage trucks, weather radars, ground radars, fixed navigation aids and other types of sensors, and is mainly used to transmit flight information with safety requirements and related to airport operations.

[0003] In order to ensure the operation of 5G AeroMACS, the site selection of 5G base stations at airports has become an important issue that needs to be solved at present. As an important transportation hub, airports gather a large number of people and have a great demand for communication services. The operating environment of airports is complex, covering multiple links such as aircraft takeoff and landing, baggage handling, and passenger pick-up. These links place extremely high demands on the immediacy and stability of communications. Since the 5G AeroMACS frequency band is relatively high, its coverage is relatively limited, so the base station location needs to be accurately selected to effectively utilize the spectrum and reduce interference. In addition, the base stations deployed at the airport need to support multiple services such as airport management, flight scheduling, and security monitoring. Reasonable base station site selection is crucial to promoting business integration and improving the overall operational efficiency of the airport. In addition, the site selection of base stations also needs to consider multiple factors such as the complex electromagnetic environment in the airport area, the ability to respond to emergencies, and economic cost-effectiveness. Summary of the invention

[0004] In view of the problems in the prior art, the present invention proposes a 5G AeroMACS system base station site selection method, which considers the base station site selection problem from three aspects: base station deployment planning, spectrum planning and network optimization. In the early stage of 5G AeroMACS construction planning, based on the ITU WRC-07 requirement that the equivalent thermal noise temperature of the fixed satellite service (FSS) system should not rise more than 2°, the equivalent isotropic radiated power (EIRP) and elevation angle of the base station and antenna can be limited. These restrictions must be considered when selecting antennas and tilt directions, and many parameters including base station location, antenna model, antenna parameters, spectrum allocation, etc. can be determined, and the corresponding coverage effect can be effectively evaluated.

[0005] The technical solution of the present invention is as follows: A 5G AeroMACS system base station site selection method includes the following steps: Step S1: Establish a digital twin model of the airport environment; Step S2: Using the DQN algorithm to maximize signal coverage and minimize interference, the optimal base station deployment parameters are obtained; Step S3: Deploy the network according to the airport 5G AeroMACS communication requirements and ICAO standards; Step S4: Optimize the network through wireless resource management and network topology optimization.

[0006] Preferably, the digital twin model in step S1 includes the following parameters: antenna type and quantity, antenna direction, antenna electrical performance parameters, antenna horizontal lobe width, operating frequency band, polarization mode, isolation, standing wave ratio, gain, transmission power, temperature, humidity, antenna downtilt angle and installation method.

[0007] Preferably, the step S2 specifically includes: Step S2-1: Set the state space, action space and reward function; Step S2-2: Establish a DQN model and train it; Step S2-3: Apply the trained DQN model to obtain the optimal base station deployment parameters.

[0008] Preferably, the state space contains a state vector S=[P,θ], where P represents the transmission power and θ represents the antenna direction; the action space contains an action A, including increasing power, reducing power and adjusting the antenna direction; the reward function is expressed as: R(S,A)=C(P,θ)-λI(P,θ)-BU(P,θ), U(P,θ) represents the operating cost, B is the balance parameter, S represents the state, A represents the action, C(P,θ) represents the coverage range, and I(P,θ) represents the interference from other users.

[0009] Preferably, the step S2-2 specifically includes: Step S2-2-1: Establish a DQN model, which consists of an input layer, a hidden layer and an output layer, wherein the hidden layer consists of multiple fully connected layers, each fully connected layer contains 128 neurons, and an activation function is used; Step S2-2-2: Set the mechanism of the DQN model learning strategy and train the DQN model.

[0010] Preferably, the mechanism of the DQN model learning strategy in step S2-2-2 includes: (1) Environmental judgment State observation: 5G base stations obtain the current state from the airport environment , including 5G base station configuration, terminal density, traffic demand and interference level; Action selection: Based on the current strategy, the 5G base station selects the action at the current moment ; ε-Greedy Strategy: Select the current best action and select a random action with probability ε; SoftMax strategy: Probabilistic selection based on action value; (2) Strategy evaluation and update Environmental feedback: After the 5G base station performs an action, the airport environment feeds back the reward signal at the current moment and the state at the next moment ; Value function update: Update the action value function Q(S,A) or the state value function V(S) based on the Bellman equation:

[0011] Where η is the learning rate and φ is the discount factor, which measures the impact of future rewards on the current strategy; Policy update: In the policy gradient method, the policy parameters are updated directly:

[0012] in, Represents the policy parameters at the current moment, represents the strategy parameters at the next moment, Indicated in Next Select probability; (3) Strategy Improvement Tune the SoftMax strategy by adjusting ε or using a decreasing temperature parameter.

[0013] Preferably, the base station deployment parameters in step S2-3 include: antenna height h, distance d between the base station and the runway, station spacing L, antenna horizontal lobe width α, antenna downtilt angle , determine the antenna coverage distance D at the far point and the antenna near point elevation angle , antenna apogee elevation angle , the minimum vertical flap width required for optimal coverage , the minimum vertical lobe width required for the antenna , the horizontal beamwidth of the antenna beam projected on the horizontal plane , the angle between the projection boundary of the antenna beam on the horizontal plane and d , the coverage blind area distance of the antenna at the airport scene Sum signal minimum incident angle .

[0014] Preferably, the step S3 specifically includes: Step tuning: 5G AeroMACS devices tune frequency in steps of 15 kHz or 30 kHz to avoid interference sources; Frequency avoidance strategy: select different frequency steps according to the amount of interference signals in the area; Multi-channel bandwidth support: supports 5 MHz, 10 MHz, 20 MHz, 30 MHz, 40 MHz and 50 MHz channel bandwidths; Dynamic bandwidth adjustment: Dynamically adjust channel bandwidth to optimize network performance based on real-time communication needs and environmental interference; Carrier aggregation: Use carrier aggregation technology to improve spectrum efficiency; Subcarrier management: A spectrum management method based on subcarrier spacing is used to balance network scanning speed and spectrum efficiency; Priority management: Prioritize security and mission-critical communications to ensure communications are maintained even under high load or interference conditions; Redundancy design: Design redundant communication links to provide backup communication paths when the channel fails or is disturbed.

[0015] Preferably, the step S4 specifically includes: Step S4-1: Implementing wireless resource management in terms of frequency scheduling, power control and interference coordination; Step S4-2: Use a ring network, a star network, and a mesh network to achieve network topology optimization.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. The 5G AeroMACS system base station site selection method proposed in the present invention can determine the optimal location of the airport 5G base station in the planning stage, covering the site spacing, antenna installation height, antenna model and parameter optimization configuration, and coverage effect evaluation, thereby avoiding the practice of base station construction based solely on experience.

[0017] 2. The 5G AeroMACS system base station site selection method proposed in the present invention can ensure that the base station performs effective spectrum allocation and interference control, and can effectively utilize wireless resources even in high-traffic and complex environments, thereby improving the network's operating efficiency and user experience.

[0018] 3. The 5G AeroMACS system base station site selection method proposed in this invention provides a highly reliable, flexible and easy-to-manage 5G communication network for airports through comprehensive network topology optimization measures, thereby meeting the airport's growing communication needs and ensuring the safety and efficiency of flight operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. The features and advantages of the present invention can be more clearly understood by referring to the drawings. The drawings are schematic and should not be understood as limiting the present invention in any way. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 It is a flow chart of the 5G AeroMACS system base station site selection method of the present invention.

[0021] Figure 2 This is a schematic diagram of intelligent dynamic parameter configuration of 5G base stations based on DQN.

[0022] Figure 3 It is a 3D model of a 5G network base station at an airport.

[0023] Figure 4 This is a schematic diagram of a 5G AeroMACS cell.

[0024] In the figure, 1-5G base station, 2-runway, 3-projection of the antenna horizontal 3 dB lobe boundary line on the horizontal plane, 4-antenna horizontal 3 dB lobe boundary line, 5-antenna beam projection boundary on the horizontal plane, 6-normal line of the antenna horizontal lobe. DETAILED DESCRIPTION

[0025] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0026] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0027] The main process of the 5G AeroMACS system base station site selection method proposed in the present invention is as follows: Figure 1 As shown in the figure, the three main aspects of base station deployment planning, spectrum planning and network optimization are considered, including: 1. Base station deployment planning; 1. In order to achieve efficient and comprehensive 5G network coverage, the deployment planning of airport 5G base stations needs to be reasonably planned, aiming to ensure smooth and safe airport communications through precise site selection and antenna deployment. In the initial planning of 5G base station deployment, site selection is a crucial first step. Base station sites are selected based on factors such as airport layout, aircraft operation routes, and airport operation area layout. Based on the requirement of 5G base station coverage radius of 500 m, terrain, buildings and other radio interference factors are taken into account to ensure that there are no blind spots in signal coverage. Site selection is accurately planned in combination with geographic information systems.

[0028] Below is a detailed plan of the antenna deployment, set into the digital twin of the airport environment: Antenna type and quantity: Select the appropriate antenna type and determine the required number of antennas based on the airport area and the actual coverage radius of the 5G base station.

[0029] Antenna Direction: Design the direction of the antenna to ensure that the signal can effectively cover the target area.

[0030] Electrical performance parameters: The electrical performance parameters of the antenna have a direct impact on the signal quality, including: Antenna horizontal beam width: 45° / 65°; Operating frequency band: 5091–5150 MHz; Polarization: ±45°; Isolation: ≥ 25; Standing wave ratio: ≤ 1.5; Gain: 16-19 dB, large linear fading of side lobes; Transmit power: 30 dBm ~ 40 dBm; Temperature: -40°~+75°; Humidity: 10%RH~95%RH; Antenna downtilt angle: 0°~15°; Installation method: Pole installation.

[0031] 2. Optimize base station deployment based on the DQN algorithm to obtain the corresponding antenna height h, distance d between the base station and the runway, station spacing L, and antenna horizontal lobe width and antenna downtilt .

[0032] Considering the actual airport environment, it is necessary to optimize the configuration of 5G base stations (such as transmit power P and antenna direction θ) to maximize signal coverage and minimize interference. The DQN algorithm can be used to dynamically adjust 5G base station parameters (such as transmit power and antenna direction) to achieve optimal signal coverage and minimize interference. Figure 2As shown in the figure, in the 5G base station deployment optimization problem, the setting of the airport environment includes the state space, action space, reward function, and the interaction process with the machine tool environment.

[0033] State space: The state vector S=[P,θ], where P represents the transmit power and θ represents the antenna direction.

[0034] Action space: Action A, increase power, decrease power, adjust antenna direction, each action corresponds to a controllable increment to adjust 5G base station parameters.

[0035] Reward function: The design of the reward function needs to balance the coverage effect and interference: R(S,A)=C(P,θ)-λI(P,θ)-BU(P,θ), where U(P,θ) represents the operating cost, B is the balancing parameter, S represents the state, A represents the action, C(P,θ) represents the coverage range, and I(P,θ) represents the interference of other users.

[0036] DQN model: The input is the state vector S=[P,θ]. The hidden layer includes multiple fully connected layers, each layer contains 128 neurons, and uses an activation function. The output layer is the action value, and the output is the expected cumulative reward for each possible action.

[0037] The following are the specific steps and mechanisms for the DQN model to learn strategies: (1) Environmental judgment State observation: The 5G base station (agent) obtains the current state from the airport environment .

[0038] Action selection: Based on the current strategy, the 5G base station (agent) selects the action at the current moment .

[0039] ε-Greedy Strategy: Choose the current best action and choose a random action (exploration) with probability ε to discover new possibilities.

[0040] SoftMax strategy: Probabilistic selection is performed based on the action value, giving a high selection probability to the better action.

[0041] (2) Strategy evaluation and update Environmental feedback: After the 5G base station (agent) performs an action, the airport environment feeds back the reward signal at the current moment and the state at the next moment The reward signal is used to evaluate the quality of the action. Positive rewards encourage similar behaviors, while negative rewards inhibit them.

[0042] Value function update: Update the action value function Q(S,A) or the state value function V(S) based on the Bellman equation:

[0043] Among them, η is the learning rate, φ is the discount factor, which measures the impact of future rewards on the current strategy, is the maximum action value of all possible actions.

[0044] Policy update: In the policy gradient method, the policy parameters are updated directly:

[0045] in, Represents the policy parameters at the current moment, represents the strategy parameters at the next moment, Indicated in Next Select This step is used to optimize the strategy so that it is more inclined to choose 5G base station deployment parameter settings that can bring higher cumulative rewards.

[0046] (3) Strategy Improvement 5G base stations continuously adjust their strategies, making the selection of 5G base station deployment parameters in different states more reasonable and effective. Strategy improvement can rely on the adjustment of the weights of the deep neural network. Maintaining a balance between exploration and utilization during the learning process is key, ensuring that 5G base stations can explore the environment to discover better strategies, while also using known information to optimize strategies. Common methods include dynamically adjusting the ε value, or using a decreasing temperature parameter to adjust the SoftMax strategy.

[0047] (4) Model training and evaluation A large number of training cycles in a simulated environment enable 5G base stations to continuously learn and optimize in different scenarios. Use techniques such as experience replay and target network to improve the stability and efficiency of training. Specifically, after the training is completed, the effectiveness of the strategy is verified by testing in a real or simulated environment. Evaluation indicators include coverage, interference level, user experience, etc. Through reinforcement learning algorithms, 5G base stations are able to dynamically adjust 5G base station deployment parameters to adapt to changing network requirements and environmental conditions.

[0048] Dynamic load balancing: When terminal density or traffic demand increases, 5G base stations can adjust the transmission power and antenna direction to optimize coverage and capacity. Interference management: 5G base stations can identify and respond to interference from neighboring base stations, and reduce interference by adjusting frequency channels or changing antenna configurations. Energy efficiency optimization: Reduce power consumption at low loads while maximizing performance at high loads. The DQN model enables 5G base stations to provide efficient and reliable network services in complex and dynamic airport environments through continuous learning and strategy optimization. This approach not only enhances the intelligent management capabilities of the network, but also provides theoretical guidance for actual deployment.

[0049] At present, factors such as the site selection, antenna operating parameters, and antenna beam width of 5G base stations at airports mainly rely on the experience of designers. From the perspective of beam morphology, the existing 5G base station antennas at airports mostly use fixed-beam plate antennas. This modified antenna is usually characterized by a wide horizontal beam (mainly 33° beam width and 65° beam width) and a narrow vertical beam (about 7°). It has a certain beamforming capability in the horizontal plane, but lacks beamforming capability in the vertical plane. In order to improve the coverage capability of the vertical beam, the existing 5G base station antennas at airports often use a 2×2 arrangement of two channels horizontally and vertically, but this will weaken the horizontal coverage capability. From the perspective of coverage holes, affected by factors such as the site of the 5G base station at the airport, antenna operating parameters, and antenna beam width, the airport is prone to coverage holes, that is, weak coverage areas, which are manifested as horizontal coverage holes and vertical coverage holes. The direct cause of the horizontal coverage holes and vertical coverage holes is that the energy distribution of the base station antenna radiation signal is directly related to the antenna pattern. Due to the existence of the antenna downtilt angle and azimuth angle, the projection of the main beam of the 5G base station radiation signal on the horizontal plane of the airport surface has a certain angle with the runway instead of completely coinciding. When the horizontal zero point of the antenna pattern is projected exactly on the runway, a horizontal coverage hole will be caused on the runway. At the same time, limited by the horizontal and vertical beamwidths of traditional plate antennas, when the projection of the main beam of the antenna pattern on the ground has a large angle with the runway, the projections of its multiple lower side lobes will also fall on the runway, and the zero point between the lobes falls on the runway, resulting in a vertical coverage hole. Usually, when designing the site of 5G base stations, antenna operating parameters, antenna beam width, etc. at airports, only the influence of the distance planning between 5G base stations and runways, the azimuth angle of the antenna and the downtilt angle are considered. In addition, it should also be ensured that the requirement that the antenna incident angle is greater than or equal to 10° is met.

[0050] Regarding the antenna azimuth and downtilt angles, for newly built 5G base stations at airports, the initial azimuth angle planning follows the upper half-power angle of the vertical lobe and the outer half-power angle of the horizontal lobe to align with the farthest coverage point; within the farthest coverage point, a switching band of about 100 to 110 meters is considered, that is, the coverage edge of each 5G network base station at the airport is the midpoint of the orbital coverage of the adjacent 5G network base station offset by 1 / 2 of the switching band position. The initial downtilt angle is determined in a similar way to the azimuth angle. The antenna upper half-power angle is used to align with the coverage edge to determine the antenna downtilt angle.

[0051] The present invention establishes a model of 5G base stations at airports, such as Figure 3 As shown. Where h is the antenna height of 5G base station 2, and d is the distance between the base station and the runway, that is, the vertical distance between the base station and runway 1. The horizontal lobe width of the 5G base station antenna is α; the near-point elevation angle of the 5G base station antenna is , the antenna far point elevation angle is ; The horizontal beam width of the antenna beam projected on the horizontal plane is ; The angle between the projection boundary 5 of the antenna beam on the horizontal plane and d is .from Figure 3 It can be seen that from the perspective of horizontal coverage, the angle between the projection boundary 5 and d of the antenna beam of the 5G base station on the horizontal plane is Determines the size of the inter-station spacing L. When the projection 3 of the antenna horizontal 3 dB lobe boundary line 4 on the horizontal plane and the intersection of the runway are used as the coverage far point, the effective coverage distance of the runway is longer; at the same time, when the projection 3 of the antenna horizontal 3 dB lobe boundary line 4 on the horizontal plane and the intersection of the runway are used as the coverage far point, the level will decay rapidly when the aircraft passes through the intersection, which is helpful for the switching of the cell. In addition to the coverage blind area distance of the antenna at the airport In addition, the effective coverage of the airport surface coverage scene line is also limited by the vertical beam width of the main beam. In order to ensure continuous coverage of the airport surface and increase the effective coverage range of the antenna, the effective coverage range of the antenna is directly affected by the vertical beam width of the antenna.

[0052] The 5G AeroMACS system base station site selection method proposed in this invention requires that the global deployment of AeroMACS will not violate the ITU WRC-07 requirement of 2° satellite temperature rise, solve the 5G base station configuration parameters of the airport, set the antenna hanging height h (including the height of the building where it is located and the height of its bracket), the distance d between the base station and the runway, the station spacing L, the antenna horizontal lobe width α, and the antenna downtilt angle , determine the antenna coverage distance D at the far point and the antenna near point elevation angle , antenna apogee elevation angle , the minimum vertical flap width required for optimal coverage , the minimum vertical lobe width required for the antenna , the horizontal beamwidth of the antenna beam projected on the horizontal plane , the angle between the projection boundary 5 of the antenna beam on the horizontal plane and d , the coverage blind area distance of the antenna at the airport scene Sum signal minimum incident angle The details are as follows:

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[0061] As attached Figure 4 As shown in the figure. This method realizes continuous and efficient wireless network coverage of runways, taxiways and other key areas by rationally selecting and optimizing the location and configuration of multiple 5G base stations (BS1, BS2, BS3, ..., BSN) in the airport. The base station location is based on the layout characteristics of the airport, the operation routes of aircraft, the distribution of buildings and possible sources of radio interference to ensure high-quality communication services without blind spots in the target area. The coverage range of each base station is determined by the directivity, transmission power and antenna parameters (such as horizontal beamwidth, vertical beamwidth, elevation angle and downtilt angle) of its antenna beam, and is accurately marked by the projection of the antenna horizontal 3 dB beam boundary line on the horizontal plane, reflecting the effective signal coverage area. The coverage ranges of the base stations overlap with each other, and redundant coverage design is implemented near the runway intersection and taxiway to improve the reliability and anti-interference capability of the system. The setting of the azimuth and downtilt angle of the antenna follows the optimization principle of the farthest coverage point and the switching band, ensuring the best coverage effect of the antenna's main signal beam in the target area. At the same time, by adjusting the step size (such as 15 kHz / 30kHz or 250 kHz) and the spectrum management strategy, it can flexibly avoid interference sources and optimize spectrum utilization and network performance. The design of the present invention effectively solves the coverage hole problem in 5G communications at airports, provides stable communication guarantee under high traffic or base station failure conditions, and significantly improves the overall efficiency and security of the airport communication network.

[0062] 2. Spectrum planning; Network deployment is carried out according to the needs of airport surface communications and relevant ICAO standards, and spectrum allocation and interference management are carried out in depth to ensure the stability and reliability of the communication system, including: Step tuning: 5G AeroMACS devices perform frequency tuning in 15 kHz / 30 kHz steps (5G standard). This allows flexibility in avoiding interference sources such as Microwave Landing System (MLS) and Aeronautical Mobile Telemetry (AMT).

[0063] Frequency avoidance strategy: Select different frequency steps according to the amount of interference signals in the area.

[0064] In high interference areas, a larger step size (e.g. 250 kHz) should be used to avoid interference quickly. In low interference areas, a smaller step size (e.g. 5 kHz to 30 kHz) may be considered to optimize spectrum utilization.

[0065] Multiple channel bandwidth support: Supports channel bandwidths of 5 MHz, 10 MHz, 20 MHz, 30 MHz, 40 MHz, and 50 MHz, with 50 MHz used by default to maximize data throughput and network efficiency.

[0066] Dynamic bandwidth adjustment: Dynamically adjust channel bandwidth to optimize network performance based on real-time communication needs and environmental interference. For example, use a larger bandwidth during high-traffic periods or high-data-demand scenarios.

[0067] Carrier aggregation: Use carrier aggregation (CA) technology to improve spectrum efficiency, achieve higher data throughput and more stable connections under multi-channel conditions.

[0068] Subcarrier management: A spectrum management method based on subcarrier spacing (SCS) is used to balance network scanning speed and spectrum efficiency. The optimal subcarrier spacing is selected according to specific application scenarios and spectrum conditions.

[0069] Priority Management: Prioritize safety-related and mission-critical communications to ensure reliable communications during high load or interference situations.

[0070] Redundant design: Whenever possible, design redundant communication links to provide backup communication paths in case the channel fails or is disturbed.

[0071] 3. Network optimization; In order to ensure that the 5G network can efficiently and stably serve the airport scene, network optimization is particularly critical. The present invention can optimize the network from the perspectives of wireless resource management and network topology optimization.

[0072] 1. Radio Resource Management Plan radio resource management strategies, including frequency scheduling, power control, and interference coordination. Ensure efficient use of radio resources in high-load and complex environments, and improve network performance and user experience. The radio resource management (RRM) strategy in 5G AeroMACS is the key to ensuring efficient use of radio resources in high-load and complex environments, and improving network performance and user experience.

[0073] (1) Frequency Scheduling 5G AeroMACS uses flexible spectrum sharing and dynamic spectrum allocation technology to adjust the allocation of spectrum resources according to real-time needs to optimize spectrum utilization. Through spectrum sensing technology, the spectrum utilization rate and network load of each 5G base station are monitored, and the spectrum allocation is adjusted in real time. For example, when the terminal demand near the terminal increases, the unused spectrum resources of the adjacent cells can be borrowed to meet the demand. In specific implementation, using software-defined radio technology, 5G base stations can adjust the spectrum configuration within milliseconds to ensure efficient use of spectrum resources and rapid response.

[0074] At the same time, 5G base stations use carrier aggregation technology to combine spectrum resources of multiple frequency bands for use, thereby providing users with higher bandwidth. In operation, 5G base stations support multi-band aggregation modules to achieve the ability to transmit multiple frequency bands simultaneously, reducing data transmission time.

[0075] (2) Power control By monitoring the signal strength and channel conditions of the terminal in real time, the transmission power of the 5G base station is dynamically adjusted. When the terminal is close to the 5G base station, the system can reduce the transmission power to save energy, and when the terminal is far away, the system will increase the power to ensure signal coverage. For example, when an aircraft is far away from the base station on the taxiway, the 5G base station automatically increases the transmission power to ensure the stability of communication, and reduces the power to reduce interference when the aircraft is close to the 5G base station.

[0076] (3) Interference coordination 5G AeroMACS introduces a variety of interference suppression and management technologies such as coordinated multi-point transmission (CoMP), multiple-input multiple-output (MIMO) and beamforming. By coordinating the transmission of multiple base stations or antenna arrays, it enhances signal quality and reduces interference between adjacent cells.

[0077] In order to reduce interference between adjacent 5G base stations, cooperative multi-point transmission technology is used. Multiple 5G base stations share the channel state information of the terminal and collaboratively provide services to the terminals at the edge of the coverage of multiple 5G base stations to enhance signal quality. Through the low-latency backhaul network, each 5G base station can quickly share information to ensure the coordination of signal transmission. For example, when the aircraft is at the edge of the taxiway and at the junction of multiple base stations, multiple 5G base stations transmit data to it at the same time, ensuring that high-quality communication signals can be obtained even in the border area.

[0078] Beamforming technology is used to focus signal energy in a specific direction based on the location of the terminal on the airport surface to improve signal strength and reduce interference. The 5G base station controls the phase and amplitude of the signal through the antenna array and dynamically adjusts the signal beam direction. For example, when the aircraft moves along the runway, the 5G base station can adjust the transmission direction of the beam in real time to ensure that the signal strength received by the terminal at different locations is always optimal, thereby providing a continuous and stable communication experience.

[0079] In addition, the 5G AeroMACS network uses artificial intelligence and machine learning technologies to effectively learn the relevant characteristics and changes of the network environment from a large amount of data, and predict network load and terminal demand by analyzing historical data and real-time network status, optimizing resource allocation strategies, and improving the network's self-organization and self-optimization capabilities. Through these comprehensive wireless resource management strategies, the 5G AeroMACS network can operate efficiently in high-load and complex environments, providing excellent network performance and user experience.

[0080] 2. Network topology optimization In the process of 5G base station site selection for airports, network topology optimization is a crucial link. The core of this process is to carefully optimize the network topology according to the traffic distribution and user needs of the airport. In order to achieve this goal, the present invention adopts a variety of network topologies, including ring networks, star networks, and mesh networks. The selection and configuration of these topologies are aimed at improving the robustness and redundancy of the network, ensuring that the network can quickly recover and switch in the face of various emergencies, such as equipment failures, link interruptions or other unexpected events, thereby ensuring the continuity and stability of communication services.

[0081] Specifically, the ring network can effectively reduce the impact of single-point failures on the overall performance of the airport network, because data can be transmitted bidirectionally in the ring structure. Even if a link fails, the data can still reach the destination through another path. The star network is simple and easy to manage, and provides efficient data transmission and centralized control capabilities in some key areas of the airport, such as terminals and control towers. The complexity and multi-path characteristics of the mesh network provide a more flexible and reliable communication solution for the airport.

[0082] In the process of network topology optimization, the following principles should be followed: Node redundancy design: Redundant nodes are set up in the airport's key communication service areas to ensure that when a node fails, other nodes can quickly take over its functions and reduce network interruption time.

[0083] Link backup: Provides backup paths for important links. When problems occur on the primary link, the backup link can immediately take over data transmission and maintain network connectivity.

[0084] Traffic balancing: Network topology design needs to achieve balanced traffic distribution to avoid performance degradation of certain nodes or links due to traffic overload.

[0085] Fault detection and response: Deploy an efficient fault detection system to quickly initiate the recovery process once a network failure is detected to ensure the continuity of network services.

[0086] Through the above comprehensive network topology optimization measures, a highly reliable, flexible and easy-to-manage 5G communication network can be provided for the airport, thereby meeting the airport's growing communication needs and ensuring the safety and efficiency of flight operations. Optimize the network topology according to traffic distribution and user needs. Use topologies such as ring networks, star networks and mesh networks to improve the robustness and redundancy of the network and ensure rapid recovery and switching in the event of a failure.

[0087] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0088] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may include that the first and second features are in direct contact, or may include that the first and second features are not in direct contact but are in contact through another feature between them. Moreover, a first feature being "above", "above" and "above" a second feature includes that the first feature is directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. A first feature being "below", "below" and "below" a second feature includes that the first feature is directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature.

[0089] In the present invention, the terms "first", "second", "third", "fourth" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance. The term "plurality" refers to two or more, unless otherwise clearly defined.

[0090] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A 5G AeroMACS system base station site selection method, characterized in that: The following steps are involved: Step S1: Establish a digital twin model of the airport environment; Step S2: Using the DQN algorithm to maximize signal coverage and minimize interference, the optimal base station deployment parameters are obtained; Step S3: Deploy the network according to the airport 5G AeroMACS communication requirements and ICAO standards; Step S4: Optimize the network through wireless resource management and network topology optimization.

2. The 5G AeroMACS system base station site selection method according to claim 1, characterized in that: The digital twin model in step S1 includes the following parameters: antenna type and quantity, antenna direction, antenna electrical performance parameters, antenna horizontal lobe width, operating frequency band, polarization mode, isolation, standing wave ratio, gain, transmission power, temperature, humidity, antenna downtilt angle and installation method.

3. The 5G AeroMACS system base station site selection method according to claim 1, characterized in that: The step S2 specifically includes: Step S2-1: Set the state space, action space and reward function; Step S2-2: Establish a DQN model and train it; Step S2-3: Apply the trained DQN model to obtain the optimal base station deployment parameters.

4. The 5G AeroMACS system base station site selection method according to claim 3, characterized in that: The state space contains a state vector S=[P,θ], where P represents the transmission power and θ represents the antenna direction; the action space contains an action A, including increasing power, reducing power and adjusting the antenna direction; the reward function is expressed as: R(S,A)=C(P,θ)-λI(P,θ)-BU(P,θ), U(P,θ) represents the operating cost, B is a balance parameter, S represents the state, A represents the action, C(P,θ) represents the coverage range, and I(P,θ) represents the interference of other users.

5. The 5G AeroMACS system base station site selection method according to claim 4, characterized in that: The step S2-2 specifically includes: Step S2-2-1: Establish a DQN model, which consists of an input layer, a hidden layer and an output layer, wherein the hidden layer consists of multiple fully connected layers, each fully connected layer contains 128 neurons, and an activation function is used; Step S2-2-2: Set the mechanism of the DQN model learning strategy and train the DQN model.

6. The 5G AeroMACS system base station site selection method according to claim 5, characterized in that: The mechanism of the DQN model learning strategy in step S2-2-2 includes: (1) Environmental judgment State observation: 5G base stations obtain the current state from the airport environment , including 5G base station configuration, terminal density, traffic demand and interference level; Action selection: Based on the current strategy, the 5G base station selects the action at the current moment ; ε-Greedy Strategy: Select the current best action and select a random action with probability ε; SoftMax strategy: Probabilistic selection based on action value; (2) Strategy evaluation and update Environmental feedback: After the 5G base station performs an action, the airport environment feeds back the reward signal at the current moment and the state at the next moment ; Value function update: Update the action value function Q(S,A) or the state value function V(S) based on the Bellman equation: Where η is the learning rate and φ is the discount factor, which measures the impact of future rewards on the current strategy. Policy update: In the policy gradient method, the policy parameters are updated directly: in, Represents the policy parameters at the current moment, represents the strategy parameters at the next moment, Indicated in Next Select probability; (3) Strategy Improvement Tune the SoftMax strategy by adjusting ε or using a decreasing temperature parameter.

7. The 5G AeroMACS system base station site selection method according to claim 6, characterized in that: The base station deployment parameters in step S2-3 include: antenna height h, distance d between the base station and the runway, station spacing L, antenna horizontal lobe width α, antenna downtilt angle , determine the antenna coverage distance D at the far point and the antenna near point elevation angle , antenna apogee elevation angle , the minimum vertical flap width required for optimal coverage , the minimum vertical lobe width required for the antenna , the horizontal beamwidth of the antenna beam projected on the horizontal plane , the angle between the projection boundary of the antenna beam on the horizontal plane and d , the coverage blind area distance of the antenna at the airport scene Sum signal minimum incident angle .

8. The 5G AeroMACS system base station site selection method according to claim 7, characterized in that: The step S3 specifically includes: Step tuning: 5G AeroMACS devices tune frequency in steps of 15 kHz or 30 kHz to avoid interference sources; Frequency avoidance strategy: select different frequency steps according to the amount of interference signals in the area; Multi-channel bandwidth support: supports 5 MHz, 10 MHz, 20 MHz, 30 MHz, 40 MHz and 50 MHz channel bandwidths; Dynamic bandwidth adjustment: Dynamically adjust channel bandwidth to optimize network performance based on real-time communication needs and environmental interference; Carrier aggregation: Use carrier aggregation technology to improve spectrum efficiency; Subcarrier management: A spectrum management method based on subcarrier spacing is used to balance network scanning speed and spectrum efficiency; Priority management: Prioritize security and mission-critical communications to ensure communications are maintained even under high load or interference conditions; Redundancy design: Design redundant communication links to provide backup communication paths when the channel fails or is disturbed.

9. The 5G AeroMACS system base station site selection method according to claim 8, characterized in that: The step S4 specifically includes: Step S4-1: Implementing wireless resource management in terms of frequency scheduling, power control and interference coordination; Step S4-2: Use a ring network, a star network, and a mesh network to achieve network topology optimization.

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