A wireless communication control method and system incorporating communication path state monitoring

Abstract

The present application relates to the technical field of wireless communication, and especially relates to a wireless communication control method and system combined with communication path state monitoring, which comprises the following steps: obtaining an original path state data set; obtaining a path section set according to the original path state data set; performing path state evaluation on each communication section in the path section set to generate a section state result; generating a section-level wireless communication control strategy in combination with a predefined service priority; executing the section-level wireless communication control strategy to obtain a real-time communication control result; and obtaining a closed-loop control result according to the real-time communication control result feedback. The present application constructs a communication path state chain through a flight path, and then generates a section-level wireless communication control strategy according to a path section state, a task control priority and multi-link availability, so that control stability and transmission efficiency are simultaneously realized in the same task, and unnecessary full-range dual-link redundancy is reduced.

Description

Technical Field

[0001] This invention relates to the field of wireless communication, and in particular to a wireless communication control method and system that combines communication path status monitoring. Background Technology

[0002] In low-altitude inspection / logistics drone corridor scenarios, the wireless communication quality of drones flying along predetermined flight paths is not uniformly varied. Instead, it is affected by a combination of factors, including overlapping coverage of multiple base stations, changes in flight altitude, changes in aircraft attitude, and switching between public and private networks. This results in significantly different communication stability in different segments of the same flight path. Existing wireless communication control methods mainly rely on single-moment signal strength, single-cell quality thresholds, or switching after a fault for link control. However, these methods are prone to switching too late in certain critical segments, leading to a sudden increase in control command latency. This results in the control plane becoming unstable even before the main link is completely interrupted, ultimately making it difficult to simultaneously guarantee continuous communication and efficient service transmission along the path. Therefore, there is an urgent need for a wireless communication control method and system that can directly incorporate communication path status monitoring results into the wireless communication control process and generate control strategies in advance according to path segments.

[0003] Existing technologies typically involve collecting measurement information such as RSRP, RSRQ, SINR, latency, and packet loss from the terminal or network side, and then reporting the measurements or switching links based on preset trigger conditions. In industry private network scenarios, this is further combined with public networks to carry services on private networks. In engineering implementation, the same approach is used: after measuring a single link, a threshold judgment is made, and finally, the switching is executed, supplemented by backup links to ensure service continuity.

[0004] Most existing solutions monitor wireless quality indicators at a single moment, single link, and single cell. While these can reflect the current link quality, they still have some drawbacks in practical use: single-link measurements are difficult to express whether there are path-level state changes such as obstruction, backhaul congestion, or insufficient neighboring cell overlap in the segments ahead that the UAV experiences as it moves continuously along the predetermined flight path; therefore, the system often can only trigger handover or remedial control after the communication quality has deteriorated significantly, lacking the ability to identify forward risk segments in advance. Summary of the Invention

[0005] This invention addresses the shortcomings of existing technologies, such as the segmented variation in wireless communication quality of UAVs along predetermined flight paths, including high-risk segments caused by building obstructions, switching gaps, and backhaul congestion. Furthermore, existing technologies often treat variations in flight speed, payload type, base station deployment density, and background interference fluctuations as noise, making it difficult to effectively distinguish between normal flight fluctuations and actual communication anomalies. This results in insufficient stability of wireless communication control across speed, scenario, and device conditions, leading to premature triggering, delayed response, and the masking of genuine low-quality segments by background fluctuations. Therefore, this invention proposes a wireless communication control method and system that incorporates communication path status monitoring.

[0006] To achieve the above objectives, on the one hand, this invention proposes a wireless communication control method and system that combines communication path status monitoring, comprising:

[0007] Obtain the original path state dataset of the drone along the predetermined flight path;

[0008] Based on the original path status dataset, the predetermined flight path is divided into multiple communication segments to obtain a path segment set;

[0009] Perform path status evaluation on each communication segment in the path segment set to generate segment status results;

[0010] Predefine service priorities and, in conjunction with the segment status results of each communication segment, generate segment-level wireless communication control strategies corresponding to each communication segment.

[0011] Within the look-ahead time window when the UAV enters the target communication segment, the segment-level wireless communication control strategy is executed to obtain real-time communication control results;

[0012] Based on the feedback of real-time communication control results, the section status results and control strategies are updated to obtain the closed-loop control results.

[0013] Preferably, the obtained path segment set includes:

[0014] Extract the continuous position sequence, serving cell identifier sequence, neighbor cell measurement sequence, altitude change sequence, occlusion scene label sequence, jitter and packet loss sequence of the UAV along the predetermined flight path from the original path state dataset;

[0015] The division points along the predetermined flight path of the UAV are obtained according to each sequence and are marked as the first division point, the second division point, the third division point, the fourth division point, and the fifth division point in sequence.

[0016] Arrange all segmentation points according to path distance, take the path segment between adjacent segmentation points as a communication segment, and ensure that the length of each communication segment is not less than the preset minimum segment length.

[0017] If the path segment length between adjacent split points is less than the minimum segment length, then the path segment is merged into the adjacent communication segment to obtain the final path segment set.

[0018] Preferably, obtaining the segmentation points existing along the predetermined flight path of the UAV includes:

[0019] Based on the serving cell identifier sequence, the points where the serving cell changes are taken as the first type of segmentation points;

[0020] Based on the neighboring area measurement sequence, the neighboring area overlap is calculated. When the neighboring area overlap between adjacent sampling points is lower than the preset overlap threshold, the corresponding position is used as the second type of segmentation point.

[0021] According to the height change sequence, when the height change exceeds the preset height change threshold, the corresponding position is used as the third type of segmentation point;

[0022] Based on the occlusion scene label sequence, when the occlusion scene label changes, the corresponding position is used as the fourth type of segmentation point;

[0023] Based on the jitter and packet loss sequence, when the delay value or packet loss rate enters the preset abnormal range, the corresponding position will be used as the fifth type of segmentation point.

[0024] Preferably, a path status assessment is performed on each communication segment in the path segment set to generate a segment status result, including:

[0025] For each communication segment, extract wireless measurement data and network load data from all sampling points within that segment;

[0026] Calculate the signal stability of this section;

[0027] Calculate the overlap margin between adjacent areas in this segment;

[0028] Calculate the delay margin for this segment;

[0029] Calculate the jitter and packet loss risk value for this segment;

[0030] Calculate the backhaul congestion load value for this section;

[0031] The signal stability, adjacent cell overlap margin, delay margin, jitter and packet loss risk value, and backhaul congestion load value of the communication segment are weighted and calculated to obtain the comprehensive state value of the communication segment, which is used as the segment state result of the segment.

[0032] Repeat the above operation until all communication segments in the path segment set have generated corresponding segment status results.

[0033] Preferably, generating segment-level wireless communication control strategies corresponding to each communication segment includes:

[0034] Predefined service priority levels are used. For each communication segment, a segment-level wireless communication control strategy is generated based on the status level of the communication segment and the transmission requirements of each priority service in the segment.

[0035] Repeat the above operation until all communication segments in the path segment set have generated corresponding segment-level wireless communication control strategies, thus obtaining the segment-level wireless communication control strategies corresponding to each communication segment.

[0036] Preferably, the predefined service priorities are as follows:

[0037] The service types in UAV missions are divided into three priority levels: the first priority is flight control commands and obstacle avoidance control, the second priority is telemetry data and status feedback, and the third priority is video transmission and payload data.

[0038] Obtain the comprehensive status value of each communication segment in the path segment set, and determine the early warning threshold R. warn and critical threshold R crit , where R crit <R warn ;

[0039] Compare the segment status result with the warning threshold R warn and critical threshold R crit The status level of the communication segment is determined by comparison, and the status level includes normal segment, warning segment and critical segment.

[0040] Preferably, the specific mapping rules for obtaining the segment-level wireless communication control strategy corresponding to each communication segment are as follows:

[0041] When the communication segment is a normal segment, the current link state is maintained for first-priority services, and the default transmission strategy is adopted for second-priority and third-priority services.

[0042] When the communication segment is a warning segment, the auxiliary link pre-establishment action is performed for the first priority service, the main link transmission is maintained for the second priority service, and the image transmission code rate is reduced or the non-critical service upload is suspended for the third priority service.

[0043] When the communication segment is a critical segment, dual-link short-term parallel action is performed for first-priority services, control plane and data plane traffic splitting action is performed for second-priority services, and rate limiting or transmission suspension action is performed for third-priority services.

[0044] Preferably, the segment-level wireless communication control strategy is executed to obtain real-time communication control results, including:

[0045] The look-ahead time window is determined based on the historical average handover time, the time for establishing and verifying secondary links, and the security redundancy time.

[0046] Obtain the current position and current flight speed of the drone, and calculate the remaining time for the drone to enter each communication segment based on the predetermined flight path;

[0047] Traverse the set of path segments. If the remaining time of a communication segment is less than or equal to the look-ahead time window, and the overall status value of the communication segment is lower than the warning threshold, then execute the segment-level wireless communication control strategy in advance.

[0048] After the control action is executed, the execution status of the control action is continuously monitored to obtain the execution result of the control action;

[0049] The execution result of the control action is correlated with the actual communication quality experienced by the UAV in the communication segment after execution, and a real-time communication control result U is generated.

[0050] If the same control strategy is executed multiple times in the same communication segment, the look-ahead time window or the triggering conditions of the control strategy corresponding to that segment will be dynamically adjusted based on the historical execution results.

[0051] On the other hand, the present invention provides a wireless communication control that combines communication path status monitoring, including the following modules:

[0052] The path status data acquisition module is used to acquire the original path status dataset of the UAV along the predetermined flight path;

[0053] The communication segment division module is connected to the path status data acquisition module and is used to divide the predetermined flight path into multiple communication segments according to the original path status dataset to obtain a path segment set.

[0054] The segment status assessment module is connected to the communication segment division module and is used to perform path status assessment on each communication segment in the path segment set and generate segment status results.

[0055] The control strategy generation module is connected to the segment status evaluation module. Based on the segment status results of each communication segment and the service priority, it generates a segment-level wireless communication control strategy corresponding to each communication segment.

[0056] The predictive execution control module, connected to the control strategy generation module, is used to execute the segment-level wireless communication control strategy corresponding to the target communication segment before the UAV is expected to enter the target communication segment, and obtain the real-time communication control result.

[0057] The feedback correction module is connected to the predictive execution control module and the segment state evaluation module. Based on the feedback of real-time control results, it updates the segment state results and control strategies to obtain closed-loop control results, and sends them back to the segment state evaluation module and the control strategy generation module.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] I. This invention constructs an original path state dataset along the predetermined flight path of an unmanned aerial vehicle (UAV), divides the continuous path into multiple communication segments according to abrupt changes in the communication environment, and comprehensively evaluates the state of each segment from five dimensions: signal stability, neighboring cell overlap margin, latency margin, jitter and packet loss risk, and backhaul congestion load. Then, based on service priority, it generates segment-level differentiated wireless communication control strategies, solving the problem that traditional wireless communication control methods rely only on single-point signal thresholds and cannot perceive changes in the communication state of forward path segments. This significantly improves the ability to identify local high-risk segments in the flight path and pre-determines differentiated control rules for services of different priorities, effectively improving the control stability of the system between different segments and avoiding high redundancy or delayed response throughout the entire process.

[0060] Second, this invention, through a look-ahead time window prediction execution and real-time communication control result feedback mechanism, enables the path segment status assessment and control strategy to maintain a high degree of consistency across speed, scenario, and device conditions. This significantly enhances the system's ability to distinguish flight fluctuations in dynamic environments, while also improving the ability to distinguish between real communication anomalies and normal flight fluctuations, reducing the risk of false triggering. As a result, the updated path segment status results and segment-level wireless communication control strategies are more stable.

[0061] Third, this invention corrects the segment state results and control strategies by rewriting the deviation between the actual observed communication quality and the predicted state in the real-time communication control results back into the segment state assessment model. This allows the segment state assessment to continuously converge to the real communication environment as the number of flights increases, further improving the system's adaptive identification capability to long-term changing environments and significantly reducing the risk of over-triggering or under-triggering of control strategies due to flight speed fluctuations, changes in payload type, and differences in network deployment. Attached Figure Description

[0062] Figure 1 This is a flowchart of the wireless communication control method of the present invention;

[0063] Figure 2 This is a structural diagram of the wireless communication control system of the present invention;

[0064] Figure 3 This is a comparison diagram of the effects of the present invention and the prior art. Detailed Implementation

[0065] To make the technical means, creative features, objectives, and effects of this invention easier to understand, the invention is further described below with reference to specific embodiments. However, the following embodiments are merely preferred embodiments of this invention and not all of them. Other embodiments obtained by those skilled in the art based on the embodiments described herein without creative effort are all within the protection scope of this invention.

[0066] Example 1:

[0067] To achieve the above objectives, please refer to Figure 1 This invention provides a wireless communication control method combining communication path status monitoring, comprising:

[0068] S1: Obtain the raw path state dataset of the UAV along the predetermined flight path.

[0069] It should be added that wireless communication control first needs to acquire UAV mission path data and wireless measurement data, integrate and process them to form a standardized dataset. The UAV onboard communication module supports 5G NR access and has 4G LTE backup capability. The system platform is deployed on edge computing nodes and interconnected with the core network and mission scheduling system.

[0070] In this embodiment, it should be specifically noted that the original path status dataset includes UAV mission path data and wireless measurement data. The UAV mission path data includes the UAV's planned flight path, which can be read through a mission planning system or a flight path planning system. The wireless measurement data includes, but is not limited to, real-time location information, flight altitude, wireless measurement values, and edge node load information. The location information and flight altitude are derived from GNSS / BeiDou, inertial navigation, or flight control systems. The wireless measurement values ​​include speed, attitude angle, neighbor cell measurement results, historical handover records, air interface latency, jitter, packet loss rate, etc., which can be obtained through the airborne communication module, base station-side measurement interface, or edge network-side logs. The edge load information usually comes from the edge computing node or the core network management interface.

[0071] As one implementation method:

[0072] Multiple 5G base stations are deployed within the drone control area to form a continuously covered drone corridor. The target drone executes a predetermined flight path to inspect power lines. The path is approximately 3.2 kilometers long, and the flight altitude can vary between 30 and 80 meters. It may pass through narrow passages between tall buildings, an open body of water, and an area with overlapping coverage of base stations.

[0073] The system obtains the UAV's planned flight path for this mission from the mission planning system or the flight path management system. The path is represented in the form of a latitude and longitude sequence. At the same time, the system obtains the UAV's current position, altitude, speed, attitude angles (pitch, roll, yaw) and other information in real time through the airborne flight control system, and sets the update frequency to 10Hz.

[0074] The airborne communication module periodically reports measurement information such as serving cell identifier, reference signal received power, reference signal received quality, signal-to-interference-plus-noise ratio, uplink / downlink delay, jitter, and packet loss rate. Simultaneously, it reports a neighboring cell measurement list, including the serving cell identifier and its reference signal received power (RSRP). This data is reported to the base station via the air interface, and then transmitted by the base station to the edge computing node via the X2 or N2 interface. The preferred reporting period Δt is 100ms to 500ms; in high-speed traversal scenarios, Δt is preferably no greater than 200ms; if the service is primarily for inspection image transmission rather than precise flight control, Δt can be relaxed to 500ms.

[0075] Extract handover events that occurred during past flights of the UAV from the logs on the edge network side, including handover start point, target cell, handover time, handover result (success / failure / hysteresis), etc., to help calibrate parameters such as look-ahead time window;

[0076] Through the management interface of the edge computing node, the CPU utilization, memory utilization, backhaul bandwidth utilization and other load data of the edge node currently connected to the drone can be obtained in real time, and the sampling period is synchronized with the wireless measurement.

[0077] All data sources are synchronized based on the Global Navigation Satellite System timestamp; the system aligns information such as position, altitude, wireless measurement, and edge load according to the sampling period based on the time sequence of UAV flight to form a continuous raw path state dataset D0.

[0078] It should be explained that D0 is stored in the form of data frames, each of which contains fields such as timestamp, latitude and longitude, altitude, speed, attitude angle, serving cell identifier and its reference signal received power, reference signal received quality, latency, jitter, packet loss rate, neighbor cell measurement list, and edge node load.

[0079] It should be added that in the park inspection scenario, the drone's cruising speed is usually 8-12 m / s. To ensure the accuracy of segment division, the reporting period Δt is preferably 200 ms, which corresponds to a spatial sampling interval of about 1.6-2.4 meters. This can capture key changes such as building obstruction and cell handover. For neighbor cell measurement reporting, when the serving cell RSRP is lower than -105 dBm or the difference between the neighbor cell RSRP and the serving cell RSRP is less than 3 dB, a measurement reporting period of 100 ms is triggered to improve the response capability to handover risks.

[0080] S2: Based on the original path status dataset, the predetermined flight path is divided into multiple communication segments to obtain a path segment set.

[0081] In this embodiment, it should be specifically explained that the process for obtaining the set of path segments is as follows:

[0082] From the original path state dataset, key sequences are extracted in chronological order, including: continuous position sequence of the UAV along the predetermined flight path, serving cell identifier sequence, neighbor cell measurement sequence, altitude change sequence, occlusion scene label sequence, and jitter and packet loss sequence;

[0083] It should be explained that the continuous location sequence includes latitude, longitude, altitude, and cumulative flight distance; the serving cell identifier sequence includes the serving cell identifier corresponding to each sampling point; the neighbor cell measurement sequence includes the neighbor cell identifier reported by each sampling point and its RSRP; the altitude change sequence includes the altitude value and its difference; the occlusion scene label sequence uses 3D map matching or synesthetic perception results to label each sampling point with scene labels such as "open area," "building occlusion," "water surface reflection," and "forest area"; and the latency and packet loss sequence includes average latency, jitter, and packet loss rate.

[0084] A sampling point refers to a set of synchronous data records collected by the system from the drone during its flight according to a fixed time period or spatial interval, and each sampling point corresponds to a complete state snapshot of the drone at a certain moment; for example, if the total length of the path is about 3.2 kilometers and the average sampling interval is about 0.2 meters, then the original path state dataset contains about 15,000 sampling points.

[0085] The segmentation points along the predetermined flight path of the UAV are obtained based on each sequence, as detailed below:

[0086] Traverse the sequence of serving cell identifiers. When the serving cell identifier of an adjacent sampling point changes, record the point of change (usually the position of the previous sampling point) as the first type of split point. For example, at a path distance of 1200 meters, the serving cell switches from 101 to 102. Here, 101 is recorded as a split point.

[0087] Based on the neighboring area measurement sequence, the neighboring area overlap is calculated for each sampling point, and adjacent sampling points are detected. If the overlap changes from above the threshold to below the threshold, the corresponding position is taken as the second type of segmentation point.

[0088] It should be explained that the neighbor cell overlap is the difference between the serving cell's RSRP and the strongest neighbor cell's RSRP. The smaller the difference, the higher the overlap. When the difference between the serving cell's RSRP and the strongest neighbor cell's RSRP is less than a preset overlap threshold, the overlap is considered higher. th When the difference is within a certain range, it indicates sufficient overlap and low risk. When the difference exceeds the preset overlap threshold O... th When this occurs, it indicates insufficient overlap, increasing risk. (O) th The value can be dynamically set based on the 25th percentile of the historical measurement samples of the route over the past 30 days. For example, in this embodiment, historical data statistics yield O. th =6dB;

[0089] The serving cell is the base station cell that the drone is currently accessing, responsible for transmitting all uplink and downlink data; the strongest neighbor cell is the cell with the highest signal strength among all neighbor cells (adjacent base station cells) that the drone can detect.

[0090] Based on the height change sequence, the difference between the height change sequences is calculated as the height change amount. When the height change amount of adjacent sampling points exceeds the preset height change threshold, the corresponding position is taken as the third type of split point. For example, the preset height change threshold can be 15m. The drone quickly climbs from 50m to 80m at a path distance of 2300m to cross a building. Here, a split point is recorded.

[0091] According to the occlusion scene label sequence, when the occlusion scene label changes, the corresponding position is used as the fourth type of segmentation point. For example, at a path distance of 450 meters, the drone enters a narrow passage between two high-rise buildings, and the label changes from "open area" to "building occlusion". A segmentation point is recorded here.

[0092] Based on the jitter and packet loss sequence, when the delay value of three consecutive sampling points exceeds the preset delay limit, or the packet loss rate exceeds the preset packet loss limit, the starting point of the abnormal interval is taken as the fifth type of segmentation point; for example, at a path distance of 2700 meters, the delay suddenly increases from 22ms to 48ms for three consecutive sampling points, and a segmentation point is recorded here.

[0093] Sort all detected split points by path distance to obtain the split point sequence [0, P1, P2, ..., P]. k L total ], where 0 is the starting point, P k Let k represent the total number of detected segmentation points, and L represent the number of segmentation points detected. totalThe path segment between adjacent split points constitutes the initial communication segment, and the length of each communication segment is not less than the preset minimum segment length.

[0094] It should be added that, in order to ensure that each segment has practical control significance and to avoid frequent strategy switching due to overly fragmented segments, the system introduces a minimum segment length. In this embodiment, the UAV's cruising speed is about 10m / s. Combined with the control strategy execution cycle, the minimum segment length is preferably 50m to 150m. If the UAV's flight speed is higher than 15m / s, the minimum segment length is preferably above 80m to avoid overly fragmented segments.

[0095] If the path segment length between adjacent split points is less than the minimum segment length, then the path segment is merged into the adjacent communication segment to obtain the final path segment set.

[0096] It should be explained that when merging path segments, since the drone's flight has a clear directionality and the path is unidirectional from the starting point to the end point, it is prioritized to merge into the previous segment. If the previous segment does not exist, it is merged into the next segment. After merging, the boundary of adjacent segments is adjusted to the main abrupt change point in the original split point to ensure that the communication environment within the segment is relatively consistent.

[0097] It is important to understand that the communication path status is not the strength of a single link at a particular moment, but rather a comprehensive reflection of the switchability, maintainability, and recoverability of multiple consecutive segments along the target path. By dividing the continuous flight trajectory into communication segments with relatively consistent coverage environments and transmission characteristics, the system can deconstruct the complex communication changes along the entire path into several independently assessable control units. This allows for the accurate identification of local high-risk segments such as building obstruction, switching gaps, and backhaul congestion, preventing single-point signals or overall average quality from masking local anomalies. This enables the system to execute differentiated control actions in advance before entering risky segments, achieving a fundamental shift from passive response to proactive prediction.

[0098] By jointly detecting the above five types of segmentation points, this invention can accurately capture and segment subtle changes in the communication environment along the flight path. For example, assuming a communication segment is only 95m long and located at the entrance of a building obstruction, marking the beginning of a dramatic change in the coverage environment, dividing it into a separate segment allows the system to trigger control strategies in advance before entering a high-risk segment. On the other hand, another communication segment is 680m long, with stable internal communication, requiring no excessive subdivision and reducing unnecessary control overhead. Compared to traditional methods of segmenting by fixed distance or fixed time, the segments divided by this invention are highly correlated with communication risks, laying the foundation for subsequent segment status assessment and precise control.

[0099] S3: Perform path status evaluation on each communication segment in the path segment set and generate segment status results.

[0100] In this embodiment, it should be specifically explained that the path status evaluation is performed on each communication segment in the path segment set to generate segment status results, which specifically includes:

[0101] For each communication segment, extract wireless measurement data and network load data from all sampling points within that segment;

[0102] Calculate the signal stability of this section;

[0103] It should be noted that signal stability reflects the fluctuation of wireless signal strength and coverage quality within a given segment. The specific calculation method can be as follows: First, calculate the mean and standard deviation of the RSRP (Resonance Ratio of Received Signals Per Second) for all sampling points within the segment. The baseline stability is defined as the ratio of the mean to the standard deviation of the RSRP. Second, calculate the proportion of sampling points within the segment whose RSRP is below a preset threshold. For example, the preset threshold could be -105 dBm. The low coverage penalty factor is defined as the difference between the value 1 and the proportion of such points. The final signal stability Q is then calculated. i It is the product of basic stability and low coverage penalty factor.

[0104] Calculate the overlap margin between adjacent areas in this segment;

[0105] It should be noted that the neighbor cell overlap margin reflects the handover availability of UAVs between the current cell and neighboring cells within the segment. It is the difference between the serving cell's RSRP and the strongest neighbor cell's RSRP (unit: dB). The smaller the difference, the higher the overlap. In this embodiment, the neighbor cell overlap margin Oi is taken as the minimum neighbor cell overlap of all sampling points within the segment, and is further corrected by considering the proportion of low-overlap sampling points. The higher the neighbor cell overlap margin, the more reliable the handover candidate cells within the segment, and the lower the risk of handover failure. Specifically, the calculation method can be: Let the number of sampling points in the segment be N, and the neighbor cell overlap of the i-th sampling point be Δi, defining Oi as... i = min(Δi) × (1 - Pl), where Pl is the proportion of sampling points with neighboring cell overlap below a preset threshold. For example, the preset threshold can be set to 6dB.

[0106] Calculate the delay margin for this segment;

[0107] It should be noted that the latency margin reflects the allowance for air interface latency within this segment relative to the service tolerance limit. Flight control commands typically require end-to-end latency to not exceed 30ms. Therefore, this embodiment presets 30ms as the latency limit T. max The specific calculation method can be: calculate the average time delay μ of all sampling points within the segment. d Define the delay margin T i =max(0, (T) max -μd ) / T max When the delay exceeds the upper limit, T i Set to 0; simultaneously, if the standard deviation of time delay within the segment σ d If the delay exceeds 5ms, a penalty is imposed on the delay jitter. The new delay margin is obtained by multiplying the delay margin by the jitter penalty factor, which can be 0.8.

[0108] Calculate the packet loss risk value for this segment, where the jitter and packet loss risk value is a weighted sum of the jitter and packet loss rates within this segment;

[0109] It should be noted that jitter and packet loss risk values ​​reflect the instability of transmission quality within this segment; the higher the value, the higher the risk. This is determined by considering the average jitter J within the segment. avg and average packet loss rate L avg Performing calculations can improve the accuracy of stability assessment within the section. The specific calculation method is as follows: J i = (J avg / J max )×w1+(L avg / L max )×w2, where J max L is the upper limit of jitter tolerance. max The upper limit for packet loss rate tolerance is w1 and w2 are weighting coefficients. For example, the upper limit for jitter tolerance can be set to 20ms, the upper limit for packet loss rate tolerance can be set to 1%, and both w1 and w2 are 0.5.

[0110] Calculate the return congestion load value L for this section. i The backhaul congestion load value is the weighted average of the loads of the edge nodes within the segment;

[0111] It should be noted that the backhaul congestion load value reflects the load status of edge computing nodes in this segment. The larger the value, the higher the risk of congestion. The system obtains the CPU utilization rate and backhaul bandwidth utilization rate of the edge nodes corresponding to all sampling points in this segment, and then takes the weighted average of the two.

[0112] After calculating the above five dimensions, the signal stability, adjacent cell overlap margin, delay margin, jitter and packet loss risk, and backhaul congestion load of the communication segment are weighted and calculated to obtain the comprehensive state value R of the communication segment. i As the segment status result for this segment, it is specifically represented as follows:

[0113]

[0114] Where R i Q represents the overall state value of the i-th communication segment; i Indicates the stability of the signal segment; O iIndicates the overlap margin between adjacent sections; T i Indicates the segment delay margin; J i Indicates the segment jitter and packet loss risk value; L i The value represents the segment's backhaul congestion load; α, β, γ, δ, and ε represent the signal stability, adjacent cell overlap margin, delay margin, jitter and packet loss risk value, and the weighting coefficients corresponding to the backhaul congestion load value, respectively, and α+β+γ+δ+ε=1.

[0115] It should be noted that for flight control main control services, γ and δ are preferably higher than α; for image transmission services, α and the weights related to throughput are preferably increased; the weights can be calibrated offline based on historical task logs by minimizing the number of out-of-control alarms, timeouts, and unnecessary switching. For example, this embodiment is a flight control priority scenario, where flight control commands require low latency and high reliability. Therefore, a higher weight is assigned to latency margin, and a higher negative weight is assigned to jitter and packet loss risk. The specific values ​​are as follows: the weight corresponding to signal stability is α = 0.20, the weight corresponding to neighbor cell overlap margin is β = 0.20, the weight corresponding to latency margin is γ = 0.30, the weight corresponding to jitter and packet loss risk value is δ = 0.20, and the weight corresponding to backhaul congestion load value is ε = 0.10.

[0116] Repeat the above operation until all communication segments in the path segment set have generated corresponding segment status results.

[0117] It's important to understand that, unlike traditional single-point measurement evaluations, this solution employs a multi-dimensional index fusion evaluation method for each communication segment. A communication segment may contain dozens to hundreds of sampling points. The system comprehensively evaluates five dimensions: signal stability, neighboring cell overlap margin, latency margin, jitter and packet loss risk, and backhaul congestion load. Each dimension corresponds to a quantitative index, and the final comprehensive segment status value R is obtained through weighted summation. i ;R i The higher the value, the better the communication status of that segment; R i The lower the value, the greater the communication risk in that segment.

[0118] S4: Predefine service priorities and, in conjunction with the segment status results of each communication segment, generate segment-level wireless communication control strategies corresponding to each communication segment.

[0119] In this embodiment, it is necessary to specifically explain the generation of segment-level wireless communication control strategies corresponding to each communication segment, as detailed below:

[0120] Based on the actual business characteristics of UAV inspection or logistics tasks, the system predefines airborne services into three priority levels, including: the first priority is flight control commands and obstacle avoidance control, the second priority is telemetry data and status feedback, and the third priority is video transmission and payload data.

[0121] It should be explained that, since UAV flight safety is the highest priority constraint, any loss, excessive delay, or error in flight control commands or obstacle avoidance control data could directly lead to the UAV going out of control, colliding, or crashing. Therefore, flight control commands and obstacle avoidance control are listed as the first priority. The timeliness requirements for this type of data are extremely stringent, and high reliability must be guaranteed. Even when the communication link quality deteriorates, the system must prioritize the transmission of this type of data, even at the cost of employing costly control methods such as dual-link redundancy and coding redundancy. In contrast, although telemetry data and status feedback are useful for mission monitoring, brief interruptions or delays generally do not immediately threaten flight safety, so they are listed as the second priority. Video transmission and payload data (such as inspection images and LiDAR point clouds) are mission outputs, and their real-time requirements are relatively relaxed, tolerating a certain degree of bitrate reduction or delayed transmission, so they are listed as the third priority.

[0122] Obtain the comprehensive status value of each communication segment in the path segment set, and determine the early warning threshold R. warn and critical threshold R crit , where R crit <R warn , where R warn The optimal value is the 20th percentile of the comprehensive state value of all historical normal sections, R. crit The 10th percentile is preferred.

[0123] Compare the segment status result with the warning threshold R warn and critical threshold R crit Based on the comparison, the communication segment is divided into three status levels, as follows:

[0124] When R i ≥R warn When this occurs, the communication segment is determined to be a normal segment. A normal segment indicates that the communication status is good and no additional control measures are required.

[0125] When R crit ≤R i <R warn When a section is identified as a warning zone, communication quality deteriorates, posing a potential risk, and preparations should be made in advance.

[0126] When R i <R crit When a critical segment is identified, the communication quality is poor, there is a clear risk, and mandatory intervention is required.

[0127] Furthermore, based on the status level of the communication segment and the transmission requirements of each priority service within the segment, a segment-level wireless communication control strategy corresponding to the communication segment is generated.

[0128] It should be noted that, based on the status level of a segment, a basic strategy framework is determined for all services within that segment. This framework defines the strength of protection for the control plane and the tolerance level for the data plane at that level. The basic strategy framework specifically includes:

[0129] In normal segments, an efficiency-first framework is adopted, maintaining only the primary link for all services without introducing additional redundancy or rate limiting. In early warning segments, a preparedness-based support framework is adopted, establishing secondary links in advance as hot backups for first-priority services and reducing the bit rate by 20% to 30% for third-priority services to address potential risks in advance. In critical segments, a mandatory redundancy framework is adopted, enabling short-term parallel transmission of dual links for first-priority services, implementing control plane and data plane splitting for second-priority services, and implementing rate limiting or suspension of transmission for third-priority services, thereby prioritizing the reliable arrival of flight control commands in segments with the worst communication conditions.

[0130] Segment-level wireless communication control strategies include at least one of the following control actions:

[0131] Maintaining the main link, pre-establishing the secondary link, short-term parallel operation of the two links, splitting the control plane and data plane, adjusting the coding redundancy level, reducing the image transmission bitrate, triggering the handover in advance, and temporarily suspending the upload of non-critical services.

[0132] It should be explained that the control actions corresponding to the communication control strategy can be combined according to the segment status and service priority, specifically including:

[0133] Main link maintenance refers to maintaining the current primary communication link's transmission status without any link switching, redundancy establishment, or rate adjustment. It is applicable to all priority services in normal segments and completes data transmission with minimal overhead.

[0134] Secondary link pre-establishment refers to activating a backup communication link (such as 4G LTE or another 5G carrier) in advance before the drone enters the warning or critical section, completing the link quality verification but not immediately transmitting service data, so as to have the ability to quickly switch when the main link is potentially deteriorated. It is mainly used for risk section protection of first priority services.

[0135] Dual-link short-term parallel refers to transmitting the same critical business data (such as flight control commands) simultaneously through the main link and the auxiliary link in the critical section, forming a redundant backup. Successful reception of any one link can guarantee the arrival of the command, greatly improving reliability. It is usually only used in very short critical sections to reduce resource consumption.

[0136] Control plane and data plane splitting refers to carrying high-reliability control plane data such as flight control commands and obstacle avoidance control on a higher-quality link, while carrying high-volume but latency-insensitive data such as image transmission and payload data on another link, thereby avoiding data plane burst traffic interference with control plane transmission.

[0137] Coding redundancy level adjustment refers to increasing the forward error correction (FEC) redundancy ratio, for example, increasing the default 10% redundancy to 20% or 30%, so that the receiver can still decode correctly when the signal quality fluctuates, and trades a certain bandwidth efficiency for transmission robustness.

[0138] Lowering the video transmission bitrate refers to reducing the encoding bitrate of video transmission, for example, from 8Mbps to 5.6Mbps, thereby reducing the occupation of wireless bandwidth, freeing up resources for control services, while still retaining basic intelligence observation capabilities.

[0139] Early handover triggering refers to proactively initiating a cell handover process before a drone enters a segment with insufficient overlap with neighboring cells, avoiding communication interruptions caused by handover delays or failures in areas with low overlap, and ensuring smooth completion of continuous changes in serving cells.

[0140] Suspending the upload of non-critical services means suspending the upload of low-priority services such as log files and non-urgent payload data (such as ordinary inspection photos), and resuming them only after leaving the risk zone, thereby concentrating wireless resources to ensure flight safety and the transmission of core mission data.

[0141] The specific mapping rules for generating segment-level wireless communication control strategies are as follows:

[0142] If the status level of the communication segment is a normal segment, the current link status is maintained for first priority services, and the default transmission strategy is adopted for second priority and third priority services, without performing additional link redundancy or flow limiting actions.

[0143] If the status level of the communication segment is a warning segment, then the auxiliary link pre-establishment action is performed for the first priority service to ensure that the control plane has a backup transmission channel before the main link deteriorates. The main link transmission is maintained for the second priority service, and the image transmission rate is reduced or the non-critical service upload is suspended for the third priority service.

[0144] If the status level of the communication segment is a critical segment, a short-term parallel action of dual links is performed for the first priority service, and control plane data is transmitted redundantly through the main link and the auxiliary link. For the second priority service, the control plane and data plane are split, and the control plane is preferentially carried on the link with better quality. For the third priority service, the rate limiting or suspension of transmission is performed until the critical segment is left.

[0145] Repeat the above operations until all communication segments in the path segment set have generated corresponding segment-level wireless communication control policies, obtaining the segment-level wireless communication control policies corresponding to each communication segment, and encapsulating the generated segment-level wireless communication control policies into a policy set C = {C1, C2, ..., C...}. n}, C i This represents the wireless communication control strategy corresponding to the i-th communication segment, where n represents the total number of communication segments. Each Ci contains the following information: Segment identifier: segment number and start and end positions; Status level: Normal / Warning / Critical; Control action list: specific actions listed according to service priority; Execution parameters: such as bitrate reduction, FEC redundancy ratio, secondary link establishment target, etc.

[0146] As one implementation method:

[0147] Statistical analysis of 30 days of flight data for this route was conducted, and the 20th percentile of the comprehensive status value for all historical normal segments was taken as the warning threshold, R. warn =3.5; take the 10th percentile as the critical threshold, R crit =2.8;

[0148] Based on S3, the segment status result corresponding to a certain communication segment is 5.59. The corresponding status level is determined to be a normal segment. The wireless communication control strategy is to maintain the main link transmission for all priority services and not perform any redundancy or rate limiting actions.

[0149] The segment status results for other communication segments were obtained as 3 and 2.6, respectively, and the corresponding status levels were identified as warning segments and critical segments. For the warning segments, the wireless communication control strategy was generated as follows: First priority: establish a 4G LTE backup link in advance; Second priority: maintain the main link transmission; Third priority: reduce the image transmission rate from 8Mbps to 5.6Mbps. For the critical segments, the wireless communication control strategy was generated as follows: First priority: transmit flight control commands simultaneously through the 5G main link and the 4G auxiliary link; Second priority: use the link with better quality for flight control commands and use another link for telemetry data; Third priority: transmit one key image frame back every 10 seconds.

[0150] This invention incorporates service importance into control decisions. Based on the status results of each segment obtained from the S3 assessment, it formulates differentiated wireless communication control strategies for each communication segment. For segments with good communication quality, efficiency is prioritized to reduce redundancy overhead. In segments with high communication risk, reliability is prioritized, key services are given priority protection, and non-key services are subject to rate limiting or load reduction, thereby achieving both control stability and transmission efficiency in the same task.

[0151] Example 1 refines the average signal quality monitoring of the entire flight path in traditional wireless link control into the state chain construction and evaluation at the path segment level. Without relying on full-length dual-link redundancy or frequent switching, it retains the local anomaly information of each communication segment, which is beneficial to improving the accuracy of continuous control along the predetermined flight path and effectively reducing the risk that wireless communication quality anomalies under conditions such as building obstruction, switching gaps, and backhaul congestion will be masked by the overall average signal.

[0152] Example 2:

[0153] This embodiment 2 further provides an improved solution based on embodiment 1. Embodiment 1 solves the problem that single-point thresholds cannot perceive the status of path segments, enabling the system to generate differentiated control strategies based on segment status results and service priorities, thereby balancing reliability and efficiency in the same task. However, in real-world application scenarios, such as different UAV models, different flight speeds, different weather conditions, different base station load states, and different time periods, the communication environment characteristics of the flight path still fluctuate significantly, resulting in a lag problem in response after link deterioration. This leads to insufficient look-ahead execution stability of the segment-level control strategy. This embodiment introduces a predictive execution and real-time communication control result feedback mechanism with a look-ahead time window based on embodiment 1. It compares the actual communication quality observation value after execution with the historical benchmark to generate a real-time communication control result U, which is used for subsequent closed-loop correction. This achieves the effect of further distinguishing between normal flight fluctuations and real communication anomalies while retaining the ability to identify local high-risk segments, further solving the defect of insufficient execution stability of segment-level control strategies under cross-speed, cross-scenario, and cross-device conditions. The specific steps are as follows:

[0154] Within the look-ahead time window when the UAV enters the target communication segment, the segment-level wireless communication control strategy is executed to obtain real-time communication control results.

[0155] In this embodiment, it is necessary to specifically explain how the real-time communication control results are obtained, as detailed below:

[0156] The look-ahead time window τ is determined based on the historical average handover duration, the duration of secondary link establishment and verification, and the safety redundancy time. pre Specifically, it is represented as: τ pre =t switch +t reserve +k; where t switch t represents the historical average handover duration. reserve τ represents the duration of secondary link establishment and verification, and k represents the safety redundancy time, preferably between 100ms and 300ms. If historical statistics show that the average handover time is 180ms and the secondary link establishment and verification time is 220ms, then τ pre The preferred setting is 500ms to 700ms;

[0157] It should be explained that the historical average handover time refers to the average time from triggering the handover command to completing the handover of the serving cell, which can be obtained by statistically analyzing the historical handover events of the flight route; the secondary link establishment and verification time refers to the average time from triggering the secondary link establishment command to the secondary link becoming available and completing quality verification. In specific applications, the UAV's onboard communication module supports simultaneous camping on 5G and 4G networks, and the average time of the secondary link establishment history is statistically analyzed. The secondary link establishment includes processes such as 4G network attachment, bearer establishment, and link quality detection; the safety redundancy time is used to offset uncertainties such as flight speed fluctuations and measurement errors. For example, combining the UAV's maximum speed of 15m / s and the system response cycle, k can be taken as 200ms.

[0158] It should be added that τ pre Setting the time too short may not allow enough time to complete the establishment or switchover preparation for the secondary link; pre Setting the value too long may prematurely consume resources or introduce unnecessary link redundancy. Therefore, the system can dynamically adjust τ according to the communication risk level of different segments. pre For the critical section, the value of k can be appropriately increased (e.g., to 300ms) to make τ pre Improvements are made by allowing more preparation time; for normal sections, even if the triggering conditions are met, the time τ can be shortened. pre To avoid preparing too early.

[0159] Based on the current time, and according to the UAV's current position coordinates and flight speed, combined with the predetermined flight path, calculate the remaining time expected for the UAV to enter each communication segment, specifically including:

[0160] Suppose the drone is currently located at a distance D from the starting point. current The location, the starting distance of the communication segment is D. starti If the current instantaneous velocity is obtained in real time through the flight control system as v, then the remaining time is approximately τ. i =(D current -D starti ) / v, when D starti ≤D current When the drone has entered or passed through the section, it will no longer trigger;

[0161] Iterate through all unvisited segments in the path segment set and calculate the remaining time τ for each communication segment. i If τ i ≤τ pre And the comprehensive state value R of this section i Below the warning threshold R warn (That is, if the segment is a warning segment or a critical segment), then the control strategy corresponding to the segment will be executed in advance.

[0162] It needs to be explained that for sections with a critical state level, the system needs to force execution triggering, even if τ i Slightly greater than τ pre This is because in this type of section, any control delay or incomplete execution may lead to loss of flight control commands, switching failure, or even loss of control of the drone. Therefore, it is necessary to ensure that all predetermined control actions (such as dual-link parallelism, control surface splitting, and redundancy coding adjustment) have been fully executed before the drone enters the boundary of the critical section, rather than starting to execute them at the boundary, so as to avoid insufficient preparation due to calculation errors.

[0163] This invention executes the segment-level wireless communication control strategy generated by S4 in advance before the UAV actually enters the target communication segment, realizing the transformation from passive response to active prediction. Based on the UAV's current position, speed and flight path, the remaining time expected to enter each segment is calculated and compared with the look-ahead time window. For segments that meet the conditions, the corresponding control actions are triggered in advance, thereby completing link preparation, code rate adjustment or switching operations before the arrival of risky segments, avoiding the need to react only after the communication quality deteriorates.

[0164] Furthermore, after the forward-looking triggering conditions are met, the control strategy for the target segment executes specific actions in sequence, and sequentially completes the confirmation and activation of the auxiliary link, the configuration of the dual-link parallel mode, the issuance of the control plane and data plane diversion rules, and the sending of non-critical business suspension instructions. Each action records the execution time, time consumption, and success or failure, thereby obtaining the control action execution result.

[0165] Subsequently, the system initiates real-time monitoring at fixed intervals (e.g., 100ms) to continuously collect link status data such as signal strength, signal-to-noise ratio, latency, and packet loss rate of the main and auxiliary links. At the same time, it tracks the end-to-end arrival confirmation of flight control commands, the reception of telemetry data packets, and the actual changes in image transmission rate. When the UAV leaves the communication segment, the system aggregates and statistically analyzes all the data collected during the monitoring period to calculate key indicators such as average latency, maximum latency, packet loss rate, and jitter in the segment, and statistically analyzes transmission performance according to service priority.

[0166] At the same time, the actual observations of this execution were compared with the baseline data of historical unstrategic flight to obtain the effect evaluation results such as the amount of time delay improvement and the reduction in packet loss rate.

[0167] Finally, all information, including the remaining time at the trigger moment, the execution sequence and duration of each control action, the observed aggregated communication quality value, the deviation from the benchmark, and any abnormal events that occurred during the period, is encapsulated into a real-time communication control result U.

[0168] For the same communication segment, after the UAV flies multiple times and executes the same control strategy, the system will dynamically adjust the look-ahead time window or the triggering conditions of the control strategy based on the accumulated historical execution results.

[0169] As one implementation method, if the total execution time of control actions is close to or exceeds the current look-ahead time window in multiple consecutive records, and the action is entered into the segment before completion, the system will increase the look-ahead time window by 10%. Conversely, if the total execution time is much less than the look-ahead time window in multiple consecutive records and no abnormalities caused by insufficient preparation have occurred, the look-ahead time window will be reduced by 5%. Similarly, if the actual communication quality is still better than expected after multiple consecutive executions of the control strategy in the same segment, the warning threshold for that segment will be adjusted downward to avoid over-control. If a flight control command timeout or link interruption occurs despite execution according to the strategy, the critical threshold will be adjusted upward, and a more aggressive strategy will be adopted before the next entry.

[0170] Based on the feedback of real-time communication control results, the section status results and control strategies are updated to obtain the closed-loop control results.

[0171] In this embodiment, it should be specifically noted that after each UAV completes a communication segment flight, the system compares the communication quality observed in the real-time communication control result U with the segment state result R predicted in step S3. i By comparing the results, the prediction deviation can be calculated.

[0172] Based on the prediction bias, the system updates the comprehensive state value R of this segment using a moving average or an exponentially weighted moving average. i And its components, and simultaneously adjust the warning threshold and critical threshold to make the state assessment closer to the real communication environment;

[0173] At the same time, the system adjusts the section-level control strategy C based on the actual execution effect of the control actions. i If a certain segment executes a high-intensity strategy multiple times but the secondary link is rarely used, the strategy is downgraded to save resources; conversely, if a low-intensity strategy still results in instruction timeouts, it is upgraded to a dual-link parallel approach or other stronger guarantees.

[0174] All updated parameters are aggregated into a closed-loop control result F and persisted to the flight route configuration file for subsequent flight missions on the same route. This mechanism enables the system to adapt to environmental changes under different seasons and network deployments, continuously converging to the optimal control strategy as the number of flights increases, gradually reducing unnecessary resource overhead while ensuring control reliability.

[0175] This embodiment corrects the segment state results and control strategies formed in Embodiment 1 by rewriting the deviation between the actual observed communication quality and the predicted state in the real-time communication control result U back into the segment state evaluation model. This allows the segment state evaluation to continuously converge to the real communication environment as the number of flights increases, further reducing the risk of over-triggering or under-triggering of the control strategy due to flight speed fluctuations, changes in payload type, and differences in network deployment. This improves the stability and resource utilization efficiency of wireless communication control under cross-scenario and cross-device conditions.

[0176] Depend on Figure 2 As shown, the present invention provides a wireless communication control system that combines communication path status monitoring, comprising the following modules:

[0177] The path status data acquisition module is used to acquire the original path status dataset of the UAV along the predetermined flight path;

[0178] The communication segment division module is connected to the path status data acquisition module and is used to divide the predetermined flight path into multiple communication segments according to the original path status dataset to obtain a path segment set.

[0179] The segment status assessment module is connected to the communication segment division module and is used to perform path status assessment on each communication segment in the path segment set and generate segment status results.

[0180] The control strategy generation module is connected to the segment status evaluation module. Based on the segment status results of each communication segment and the service priority, it generates a segment-level wireless communication control strategy corresponding to each communication segment.

[0181] The predictive execution control module, connected to the control strategy generation module, is used to execute the segment-level wireless communication control strategy corresponding to the target communication segment before the UAV is expected to enter the target communication segment, and obtain the real-time communication control result.

[0182] The feedback correction module is connected to the predictive execution control module and the segment state evaluation module. Based on the feedback of real-time control results, it updates the segment state results and control strategies to obtain closed-loop control results, and sends them back to the segment state evaluation module and the control strategy generation module.

[0183] Depend on Figure 3It is evident that, compared to existing technologies, this invention demonstrates superior performance in terms of identifying local high-risk segments, characterizing risk distribution, distinguishing normal flight fluctuations, and maintaining control stability across speeds and scenarios. Specifically, this invention improves the identification capability of local high-risk segments under conditions of low coverage, high interference, and handover gaps through communication segment division and segment status assessment. Furthermore, through a look-ahead time window prediction execution and real-time communication control result feedback mechanism, it further mitigates the interference of flight speed changes, payload type differences, base station deployment density differences, and background interference changes on the control results, thereby making the updated path segment status results and segment-level wireless communication control strategies more stable.

[0184] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A wireless communication control method combining communication path status monitoring, characterized in that, include: Obtain the original path state dataset of the drone along the predetermined flight path; Based on the original path status dataset, the predetermined flight path is divided into multiple communication segments to obtain a path segment set; Perform path status evaluation on each communication segment in the path segment set to generate segment status results; Predefine service priorities and, in conjunction with the segment status results of each communication segment, generate segment-level wireless communication control strategies corresponding to each communication segment. Within the look-ahead time window when the UAV enters the target communication segment, the segment-level wireless communication control strategy is executed to obtain real-time communication control results; Based on the feedback of real-time communication control results, the section status results and control strategies are updated to obtain the closed-loop control results.

2. The wireless communication control method according to claim 1, characterized in that: The obtained set of path segments includes: Extract the continuous position sequence, serving cell identifier sequence, neighbor cell measurement sequence, altitude change sequence, occlusion scene label sequence, jitter and packet loss sequence of the UAV along the predetermined flight path from the original path state dataset; The division points along the predetermined flight path of the UAV are obtained according to each sequence and are marked as the first division point, the second division point, the third division point, the fourth division point, and the fifth division point in sequence. Arrange all segmentation points according to path distance, take the path segment between adjacent segmentation points as a communication segment, and ensure that the length of each communication segment is not less than the preset minimum segment length. If the path segment length between adjacent split points is less than the minimum segment length, then the path segment is merged into the adjacent communication segment to obtain the final path segment set.

3. The wireless communication control method according to claim 2, characterized in that: The acquisition of the segmentation points existing along the predetermined flight path of the UAV includes: Based on the serving cell identifier sequence, the points where the serving cell changes are taken as the first type of segmentation points; Based on the neighboring area measurement sequence, the neighboring area overlap is calculated. When the neighboring area overlap between adjacent sampling points is lower than the preset overlap threshold, the corresponding position is used as the second type of segmentation point. According to the height change sequence, when the height change exceeds the preset height change threshold, the corresponding position is used as the third type of segmentation point; Based on the occlusion scene label sequence, when the occlusion scene label changes, the corresponding position is used as the fourth type of segmentation point; Based on the jitter and packet loss sequence, when the delay value or packet loss rate enters the preset abnormal range, the corresponding position will be used as the fifth type of segmentation point.

4. The wireless communication control method according to claim 1, characterized in that: For each communication segment in the set of path segments, a path status assessment is performed to generate a segment status result, including: For each communication segment, extract wireless measurement data and network load data from all sampling points within that segment; Calculate the signal stability, adjacent cell overlap margin, delay margin, jitter and packet loss risk value, and backhaul congestion load value of this segment; The signal stability, adjacent cell overlap margin, delay margin, jitter and packet loss risk value, and backhaul congestion load value of the communication segment are weighted and calculated to obtain the comprehensive state value of the communication segment, which is used as the segment state result of the segment. Repeat the above operation until all communication segments in the path segment set have generated corresponding segment status results.

5. The wireless communication control method according to claim 1, characterized in that: Generate segment-level wireless communication control strategies corresponding to each communication segment, including: Predefined service priority levels are used. For each communication segment, a segment-level wireless communication control strategy is generated based on the status level of the communication segment and the transmission requirements of each priority service in the segment. Repeat the above operation until all communication segments in the path segment set have generated corresponding segment-level wireless communication control strategies, thus obtaining the segment-level wireless communication control strategies corresponding to each communication segment.

6. The wireless communication control method according to claim 5, characterized in that: The predefined service priorities are as follows: The service types in UAV missions are divided into three priority levels: the first priority is flight control commands and obstacle avoidance control, the second priority is telemetry data and status feedback, and the third priority is video transmission and payload data. Obtain the comprehensive status value of each communication segment in the path segment set, and determine the early warning threshold R. warn and critical threshold R crit , where R crit <R warn ; Compare the segment status result with the warning threshold R warn and critical threshold R crit The status level of the communication segment is determined by comparison, and the status level includes normal segment, warning segment and critical segment.

7. The wireless communication control method according to claim 5, characterized in that: The specific mapping rules for obtaining the segment-level wireless communication control strategy corresponding to each communication segment are as follows: When the communication segment is a normal segment, the current link state is maintained for first-priority services, and the default transmission strategy is adopted for second-priority and third-priority services. When the communication segment is a warning segment, the auxiliary link pre-establishment action is performed for the first priority service, the main link transmission is maintained for the second priority service, and the image transmission code rate is reduced or the non-critical service upload is suspended for the third priority service. When the communication segment is a critical segment, dual-link short-term parallel action is performed for first-priority services, control plane and data plane traffic splitting action is performed for second-priority services, and rate limiting or transmission suspension action is performed for third-priority services.

8. The wireless communication control method according to claim 1, characterized in that: Executing the segment-level wireless communication control strategy yields real-time communication control results, including: The look-ahead time window is determined based on the historical average handover time, the time for establishing and verifying secondary links, and the security redundancy time. Obtain the current position and current flight speed of the drone, and calculate the remaining time for the drone to enter each communication segment based on the predetermined flight path; Traverse the set of path segments. If the remaining time of a communication segment is less than or equal to the look-ahead time window, and the overall status value of the communication segment is lower than the warning threshold, then execute the segment-level wireless communication control strategy in advance.

9. The wireless communication control method according to claim 8, characterized in that: Also includes: After the control action is executed, the execution status of the control action is continuously monitored to obtain the execution result of the control action; The execution result of the control action is correlated with the actual communication quality experienced by the UAV in the communication segment after execution, and a real-time communication control result U is generated. If the same control strategy is executed multiple times in the same communication segment, the look-ahead time window or the triggering conditions of the control strategy corresponding to that segment will be dynamically adjusted based on the historical execution results.

10. A wireless communication control system incorporating communication path status monitoring, used to execute the wireless communication control method as described in any one of claims 1-9, characterized in that, include: The path status data acquisition module is used to acquire the original path status dataset of the UAV along the predetermined flight path; The communication segment division module is connected to the path status data acquisition module and is used to divide the predetermined flight path into multiple communication segments according to the original path status dataset to obtain a path segment set. The segment status assessment module is connected to the communication segment division module and is used to perform path status assessment on each communication segment in the path segment set and generate segment status results. The control strategy generation module is connected to the segment status evaluation module. Based on the segment status results of each communication segment and the service priority, it generates a segment-level wireless communication control strategy corresponding to each communication segment. The predictive execution control module, connected to the control strategy generation module, is used to execute the segment-level wireless communication control strategy corresponding to the target communication segment before the UAV is expected to enter the target communication segment, and obtain the real-time communication control result. The feedback correction module is connected to the predictive execution control module and the segment state evaluation module. Based on the feedback of real-time control results, it updates the segment state results and control strategies to obtain closed-loop control results, and sends them back to the segment state evaluation module and the control strategy generation module.

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