Multidirectional communication data forwarding method and system

Abstract

The invention relates to the technical field of information, and mainly aims to guarantee the communication continuity and data integrity of villages in remote mountainous areas. The invention provides a multidirectional communication data forwarding method and system, and the method comprises the steps: obtaining terrain elevation data and mountain surface reflection characteristics, constructing a three-dimensional terrain simulation environment, calculating an initial visible range between communication nodes, and obtaining a preliminary signal propagation interference distribution diagram; obtaining signal time difference data of each path in the preliminary forwarding path scheme, and generating an optimized forwarding path set; monitoring the distribution change of communication nodes of the forwarding path set in real time, continuously monitoring the change trend of signal propagation interference, determining signal loss rate data in a path execution process, and generating a stable communication transmission channel; according to a stable communication transmission channel, a signal time difference change trend in a path switching process is analyzed, and a switching time interval, a signal strength threshold and a node load balancing coefficient of path switching are determined.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to a multi-directional communication data forwarding method and system. Background Art

[0002] Establishing a stable and reliable multi-directional communication network in complex mountainous terrain, overcoming the adverse effects of terrain obstacles on signal propagation, and ensuring stable and continuous data transmission has become a critical issue in the field of communications technology. Although various communication forwarding strategies have been proposed and applied in mountainous environments, these approaches often overlook the profound impact of dynamic terrain changes on signal propagation. In particular, they lack in-depth consideration of environmental adaptability when faced with complex conditions such as mountain obstruction and signal reflections. More importantly, these solutions often focus on fixed path planning or local optimization of a single signal source, failing to effectively address the sudden obstructions and frequent changes in signal propagation paths caused by the undulating mountain terrain at the system level. This results in limited communication coverage, low data transmission efficiency, and a failure to meet the actual communication needs in complex mountainous environments. The primary challenge lies in the intermittent reduction in visibility between communication nodes caused by mountain obstruction. This terrain obstruction makes it difficult to maintain long-term stability of signal transmission paths within direct line of sight, increasing the risk of packet loss and making the network topology highly dynamic and uncertain. The highly dynamic and uncertain network topology causes signal arrival time variations. This multipath propagation phenomenon not only causes signal interference and attenuation, but also significantly reduces data synchronization accuracy, making it difficult for communication nodes to accurately determine and select the optimal data forwarding path in a dynamically changing environment. Therefore, designing a dynamically adjusted data forwarding path selection strategy in complex mountainous terrain, addressing visibility discontinuities caused by mountain obstruction and signal time variations caused by mountain reflections, has become a key issue in ensuring communication continuity and data integrity in remote mountain villages. Summary of the Invention

[0003] The present invention provides a multi-directional communication data forwarding method, which mainly includes: Obtain terrain elevation data and mountain surface reflection characteristics, build a three-dimensional terrain simulation environment, calculate the initial visible range between each communication node, and obtain a preliminary signal propagation interference distribution map; based on the preliminary signal propagation interference distribution map, identify areas with discontinuous visible ranges, collect reflected signals and scattered signals in areas with discontinuous visible ranges, and determine the location interval of the interfered communication nodes based on the signal time difference; obtain the terrain obstruction degree and signal strength attenuation of the location interval of the interfered communication nodes, identify the main signal propagation interference source based on the terrain obstruction degree, and determine the dynamic interference weight factor based on the distance between nodes and the complexity of the terrain; construct a candidate set of data forwarding paths based on the dynamic interference weight factor, and conduct feasibility assessment and interference intensity evaluation. Sorting, extracting alternative paths that meet the communication quality requirements, screening out the path combination with the least signal propagation interference by calculating the path length change rate and node connectivity change rate of the alternative paths, and determining the preliminary forwarding path plan; obtaining the signal time difference data of each path in the preliminary forwarding path plan, and generating an optimized forwarding path set; real-time monitoring of the changes in the communication node distribution of the forwarding path set, continuously monitoring the changing trend of signal propagation interference, determining the signal loss rate data during the path execution process, and generating a stable communication transmission channel; based on the stable communication transmission channel, analyzing the changing trend of the signal time difference during the path switching process, and determining the switching time interval, signal strength threshold, and node load balancing coefficient for path switching.

[0004] Furthermore, the acquisition of terrain elevation data and mountain surface reflection characteristics, the construction of a three-dimensional terrain simulation environment, the calculation of the initial visibility range between each communication node, and the acquisition of a preliminary signal propagation interference distribution map include: By scanning, point cloud data of mountain terrain is acquired, a digital elevation matrix is ​​generated, the altitude value of each grid cell is recorded, the material information of the mountain surface is collected, the electromagnetic wave reflection coefficient of each grid cell is determined, and a three-dimensional terrain database containing elevation information and electromagnetic wave reflection coefficient is constructed; based on the latitude and longitude coordinates and elevation information of the distribution location of the communication nodes, the spatial position of each node is located in the three-dimensional terrain database, the terrain elevation profile data on the node connection path is extracted, and an initial visible node set of each node is generated; based on the distance and transmission power between the nodes in the initial visible node set, the free space propagation loss is calculated, and the electromagnetic wave propagation path is tracked in combination with the electromagnetic wave reflection coefficient, the reflected wave intensity is calculated, the direct signal intensity and the reflected signal intensity are superimposed to generate a composite signal strength value for each node; based on the composite signal strength value, a preliminary signal propagation interference distribution map covering the entire mountain area is generated through spatial interpolation operation.

[0005] Furthermore, the identifying of areas with discontinuous visibility ranges based on the preliminary signal propagation interference distribution map, collecting reflected signals and scattered signals from the areas with discontinuous visibility ranges, and determining the location interval of the interfered communication nodes based on signal time differences includes: According to the preliminary signal propagation interference distribution map, the signal strength values ​​of adjacent grid cells are scanned, the discontinuity points where the signal strength difference exceeds the threshold are marked, the continuous discontinuity points are connected to form a discontinuity boundary line, and a set of geographic coordinates of the discontinuity area in the visible range is generated; sampling points are selected from the geographic coordinate set, signals from communication nodes are received, the amplitude variation sequence of the signals from the communication nodes is recorded over time, the arrival times of the direct signal, the reflected signal and the scattered signal are detected, the time difference between the reflected signal and the direct signal and the time difference between the scattered signal and the direct signal are calculated, and a multipath time delay difference table is generated; according to the multipath time delay difference table, combined with the electromagnetic wave propagation speed and terrain elevation data, the surface position coordinates of the reflecting mountain are determined by the positioning principle, the signal transmission path is traced back, and the position interval of the interfered communication node is determined.

[0006] Furthermore, the obtaining of the terrain shielding degree and the signal strength attenuation in the location interval of the interfered communication node and identifying the main signal propagation interference source according to the terrain shielding degree includes: Extract terrain elevation sampling points within the interfered communication node location interval, calculate the difference between the node location elevation and the sampling point elevation, and count the proportion of sampling points with positive elevation difference as the terrain blocking degree coefficient; measure the actual received signal strength in the interfered communication node location interval, compare it with the theoretical signal strength, and generate the signal strength attenuation; divide the space around the node into multiple sectors according to the terrain blocking degree coefficient and the signal strength attenuation, calculate the product value of the blocking degree coefficient and the signal strength attenuation of each sector, select the sector with the largest product value, determine the mountain in the direction of the sector as the main signal propagation interference source, and generate the interference source azimuth distribution data.

[0007] Furthermore, the method of constructing a data forwarding path candidate set based on the dynamic interference weight factor, performing feasibility assessment and interference intensity sorting, and extracting candidate paths that meet communication quality requirements includes: According to the dynamic interference weight factor, adjacent node pairs in the communication network are traversed, and node pairs with weight factors lower than a threshold are marked as available links. All reachable paths from the starting node to the receiving node are searched, and the path node sequence and link weight factor sequence are recorded to generate a data forwarding path candidate set; according to the data forwarding path candidate set, the link weight factor of each path is accumulated to generate a total path interference value, and the paths with total interference values ​​lower than the threshold are retained as feasible paths. The paths are sorted according to the total interference value, and the paths with the smallest interference value are selected as the alternative path set.

[0008] Furthermore, after selecting the path with the smallest interference value as the candidate path set, the following steps are performed: For each path in the alternative path set, the ratio of the number of link segments contained in the path to the minimum number of link segments is calculated to generate a path length change rate; the number of adjacent nodes that each relay node in the alternative path set can reach after the path is removed is counted, and the ratio of this number to the number before removal is calculated to generate a node connectivity change rate; based on the sum of the path length change rate and the node connectivity change rate, the path with the smallest sum is selected to generate a path combination with minimal signal propagation interference.

[0009] Furthermore, generating the optimized forwarding path set includes: For each path in the forwarding path plan, a test signal is sent, the time when the signal arrives at each relay node and the end point is recorded, the difference between the propagation time between adjacent nodes and the theoretical time is calculated, and signal time difference data is generated; based on the signal time difference data, the time difference values ​​of all link segments on the path are accumulated to generate the total path delay deviation, and a search is conducted around the midpoint of the link segment with the largest time difference value for a location with a higher altitude and no obstruction to generate a replacement relay node position; based on the replacement relay node position, the path configuration is updated, the signal propagation loss is measured, the transmitting node power is adjusted, and an optimized forwarding path set is generated.

[0010] Furthermore, the real-time monitoring of changes in the distribution of communication nodes in the forwarding path set, the continuous monitoring of the changing trend of signal propagation interference, the determination of signal loss rate data during the path execution process, and the generation of a stable communication transmission channel include: Real-time monitoring of the online status and location coordinates of each node in the optimized forwarding path set, recording changes in node distribution, measuring deviations in signal strength and latency, and generating data on signal propagation interference change trends. Based on the data, the signal loss rate of the path is calculated, and the alternative path with the highest signal strength is selected as the replacement path. Based on the replacement path, the transmission configuration is updated, a new next-hop node address is sent, and a stable communication transmission channel is generated.

[0011] Furthermore, the method of analyzing the trend of signal time difference changes during the path switching process based on the stable communication transmission channel to determine the switching time interval, signal strength threshold, and node load balancing coefficient for the path switching includes: Extract the moment of the path switching event and the signal propagation time in the stable communication transmission channel, calculate the time difference before and after the switching, and generate signal time difference change data; calculate the time difference standard deviation based on the signal time difference change data, determine the switching recovery time, and generate the switching time interval for the path switching; extract the signal strength value when the switching is triggered, and generate a signal strength threshold; count the number of data packets forwarded by each node, calculate the ratio of the node forwarding amount to the average forwarding amount, and generate a node load balancing coefficient.

[0012] The present invention provides a multi-directional communication data forwarding system, which mainly includes: a terrain data acquisition module, which is used to obtain terrain elevation data and mountain surface reflection characteristics, build a three-dimensional terrain simulation environment, calculate the initial visible range between each communication node, and obtain a preliminary signal propagation interference distribution map; an interference area identification module, which is used to identify the area with discontinuity in the visible range according to the preliminary signal propagation interference distribution map, collect the reflected signal and scattered signal in the area with discontinuity in the visible range, and determine the position interval of the interfered communication node according to the signal time difference; an interference source analysis module, which is used to obtain the terrain shielding degree and signal strength attenuation of the position interval of the interfered communication node, identify the main signal propagation interference source according to the terrain shielding degree, and determine the dynamic interference weight factor according to the distance between nodes and the terrain complexity; a path candidate set construction module, which is used to construct a data forwarding system according to the dynamic interference weight factor A set of candidate paths is generated, and feasibility assessment and interference intensity ranking are performed to extract alternative paths that meet the communication quality requirements. By calculating the path length change rate and node connectivity change rate of the alternative paths, the path combination with the least signal propagation interference is screened out to determine the preliminary forwarding path plan; a path optimization module is used to obtain the signal time difference data of each path in the preliminary forwarding path plan and generate an optimized forwarding path set; a communication monitoring module is used to monitor the changes in the communication node distribution of the forwarding path set in real time, continuously monitor the changing trend of signal propagation interference, determine the signal loss rate data during the path execution process, and generate a stable communication transmission channel; a channel stability analysis module is used to analyze the changing trend of the signal time difference during the path switching process based on the stable communication transmission channel, and determine the switching time interval, signal strength threshold and node load balancing coefficient of the path switching. The technical solution provided by the embodiment of the present invention may include the following beneficial effects: The present invention discloses a multi-directional communication data forwarding method and system. The method performs three-dimensional modeling of mountain terrain, constructs a simulation environment, calculates the initial visible range between communication nodes, and obtains a radio communication signal propagation interference distribution map. According to the interference distribution, the visible range discontinuity area is identified, the mountain reflection effect is analyzed, and the location of the interfered node is determined. Based on the degree of terrain obstruction and signal attenuation, the main interference source is identified and the dynamic interference weight factor is determined. The candidate set of data forwarding paths is constructed and evaluated, and the path combination with the least interference is screened out. By monitoring the signal time difference in real time, the relay node position and transmission power are dynamically adjusted to optimize the forwarding path. At the same time, a path switching mechanism is established to enhance environmental adaptability and achieve stable communication transmission. The present invention can effectively solve the communication interference problem caused by complex mountain terrain and improve communication quality and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 The present invention is a flowchart of a multi-directional communication data forwarding method.

[0014] Figure 2 It is a structural diagram of a multi-directional communication data forwarding system of the present invention. DETAILED DESCRIPTION

[0015] The following will describe the technical solutions in the embodiments of the present invention in detail with reference to the accompanying drawings. The described embodiments are only a part of the embodiments of the present invention.

[0016] like Figure 1-Figure 2 As shown, a multi-directional communication data forwarding method and system of this embodiment may specifically include: S101, obtain terrain elevation data and mountain surface reflection characteristics, build a three-dimensional terrain simulation environment, calculate the initial visibility range between each communication node, and obtain a preliminary signal propagation interference distribution map.

[0017] LiDAR scanning acquires mountain terrain point cloud data, which is then rasterized to generate a digital elevation matrix. Each grid cell records the altitude of the corresponding location. Mountain surface material information is also collected, and the electromagnetic wave reflection coefficient of each grid cell is determined based on rock, soil, and vegetation cover types. A three-dimensional terrain database containing both elevation information and electromagnetic wave reflection coefficients is constructed. The spatial position of each communication node is located within the 3D terrain database based on its longitude and latitude coordinates and elevation information. For each pair of node paths, terrain elevation profile data along the path is extracted. Using the principles of geometric optics, the presence of mountain obstructions between nodes is determined. If the terrain elevation of any point on the path exceeds the node connection height, the node pair is deemed invisible, resulting in an initial visible node set for each node. For each pair of nodes in the initial visible node set, the free-space propagation loss L = 32.45 + 20log(f) + 20log(d) is calculated based on the inter-node distance d and the transmission power P, where f is the communication frequency. The electromagnetic wave propagation path is traced along the node line, combining the electromagnetic wave reflection coefficient along the propagation path. When the electromagnetic wave encounters the terrain surface, the reflected wave intensity is calculated based on the incident angle and reflection coefficient. The direct signal intensity and the reflected signal intensity are superimposed according to the phase relationship to obtain the composite signal strength value at the receiving point. Based on the composite signal strength value between each node pair, spatial interpolation is performed on the grid cells of the three-dimensional terrain database. For grid cells at non-node locations, the inverse distance weighted method is used to calculate the signal strength estimate of the grid based on the signal strength values ​​of surrounding nodes. The signal strength values ​​of all grid cells are color-coded according to the intensity level, generating a preliminary signal propagation interference distribution map covering the entire mountainous area.

[0018] Specifically, in the process of digital modeling of mountainous terrain, lidar scanning technology acquires high-precision three-dimensional point cloud data by emitting laser pulses and receiving ground reflection signals.

[0019] Specifically, a LiDAR device, mounted on an aircraft, emits a laser beam toward the ground at a fixed scanning frequency. When the laser beam hits the mountain surface and reflects back, the precise location of the ground point is determined by calculating the time difference between the laser's round trip and the ground. This scanning method can penetrate the vegetation canopy and obtain true surface elevation information, making it particularly suitable for surveying complex mountainous terrain. Rasterization is a key step in converting irregularly distributed point cloud data into a regular grid structure.

[0020] In one possible implementation, the entire mountainous area is divided into 10m x 10m grid cells. Each grid cell may contain multiple laser points, and the average elevation of these points is calculated as the representative elevation of the grid cell. The surface material type is also determined based on the laser reflection intensity. The reflection intensity of rock surfaces is typically between 0.7 and 0.9, that of soil surfaces is 0.3 to 0.5, and that of vegetation-covered areas is in the range of 0.1 to 0.3. These reflection coefficients directly affect the propagation characteristics of electromagnetic waves.

[0021] It should be noted that the application of geometric optics principles is crucial when judging the visibility between nodes.

[0022] For example, when two communication nodes are located on both sides of a valley, it is necessary to check the terrain elevation point by point along the direction of the node connection. Assume that node A is located at an altitude of 1500 meters and node B is located at an altitude of 1600 meters. The horizontal distance between the two nodes is 5 kilometers, and an elevation sampling point is extracted every 50 meters on the connection path. If the terrain elevation of a sampling point is 1800 meters, and the line of sight height at that point is only 1550 meters, it indicates that there is a mountain obstruction and the two nodes are invisible. This judgment method ensures the accuracy of subsequent signal propagation calculations. In the signal propagation calculation, the free space propagation loss formula L=32.45+20log(f)+20log(d) describes the attenuation law of electromagnetic waves in an unobstructed space.

[0023] Preferably, when the communication frequency f is 900 MHz and the propagation distance d is 5 km, the free space loss is approximately 113 dB. However, actual propagation in mountainous environments is more complex. Electromagnetic waves will be reflected when encountering the mountain surface. When the reflected wave and the direct wave are superimposed at the receiving point, constructive or destructive interference may occur. If the direct wave intensity is -80 dBm, the reflected wave will attenuate to -85 dBm after reflection from the mountain. When the phase difference between the two is 180 degrees, destructive interference will occur, causing the received signal strength to drop below -86 dBm. The inverse distance weighted interpolation method plays an important role in generating signal distribution maps.

[0024] In one embodiment, for any grid point that is not a node, its signal strength is calculated by taking the weighted average of the signal strengths of surrounding known nodes, with the weight being inversely proportional to the square of the distance. Nodes that are closer contribute more to the signal strength of that point. This method can reasonably reflect the impact of mountainous terrain on signal propagation. The generated interference distribution map uses different colors to represent signal strength levels. Red areas represent good coverage areas with signal strengths above -70dBm, yellow areas represent general coverage areas with signal strengths between -70 and -90dBm, and blue areas represent weak coverage areas with signal strengths below -90dBm, providing an intuitive reference for subsequent network optimization.

[0025] S102, based on the preliminary signal propagation interference distribution map, identifying the area where the visible range is discontinuous, collecting the reflected signal and scattered signal in the area where the visible range is discontinuous, and determining the position interval of the interfered communication node based on the signal time difference.

[0026] Based on a preliminary signal propagation interference distribution map, the signal strength values ​​of adjacent grid cells are scanned. If the difference in signal strength between adjacent grid cells exceeds a preset threshold, the cells are marked as visible range discontinuities. Consecutive discontinuity points are connected to form a discontinuity boundary line. The boundary line encloses the spatial extent of the visible range discontinuity region and its geographic coordinate set. Sampling points are selected from the geographic coordinate set of the visible range discontinuity region. For each sampling point, a signal from a communication node is received. The amplitude of the received signal is recorded over time. Peak detection is used to identify the arrival times of the direct signal, the mountain reflection signal, and the edge scattered signal. The time difference between the reflected signal and the direct signal is calculated, as well as the time difference between the scattered signal and the direct signal. This creates a multipath delay difference table for each sampling point. According to the time difference data in the multipath delay difference table, the time difference is multiplied by the electromagnetic wave propagation speed to obtain the distance difference between the reflected path and the direct path. Combined with the sampling point coordinates and the mountain terrain elevation data, the hyperbola positioning principle is used to determine the position coordinates of the mountain surface where the reflection occurs. According to the mountain reflection position, the sampling point position and the law of electromagnetic wave incidence and reflection, the signal transmission path is traced back to determine the position interval of the interfered communication node.

[0027] Specifically, in a mountainous communication environment, a sharp change in signal strength often indicates the presence of terrain blocking or multipath interference.

[0028] Specifically, when scanning the signal propagation interference distribution map, if the signal strength between adjacent 10m x 10m grid cells drops suddenly from -70dBm to -95dBm, this 25dB difference far exceeds the normal attenuation range, indicating a discontinuity in visibility. By connecting these discontinuities to form a boundary line, the specific area affected by the mountain barrier can be accurately delineated.

[0029] It should be noted that these discontinuous areas are precisely where the multipath propagation phenomenon is most complex.

[0030] In one possible implementation, when selecting multiple sampling points within a discontinuous region for signal measurement, the received signals exhibit distinct differences in their time-domain characteristics. The direct signal, as the first component to arrive, has the strongest amplitude and a complete waveform. The subsequent mountain-reflected signal, due to the additional propagation path, is not only attenuated in intensity but also delayed by several microseconds. The edge-scattered signal, on the other hand, appears as a superposition of multiple small-amplitude pulses, with a longer time delay and a more dispersed distribution. Peak detection plays a key role in distinguishing these signals from different paths.

[0031] For example, when the first peak exceeding three times the noise threshold appears in the amplitude sequence of the received signal, this moment is recorded as t1, i.e., the arrival time of the direct signal; continue to monitor subsequent signals, and when a second obvious peak appears and the amplitude exceeds two times the noise threshold, it is recorded as t2, which is the arrival time of the reflected signal; the time difference between the two, t2-t1, is the additional propagation delay of the reflected path relative to the direct path.

[0032] Advantageously, the application of the hyperbolic positioning principle makes it possible to deduce node location from delay information. Considering that electromagnetic waves propagate through air at a speed of 300,000 kilometers per second, a delay of 1 microsecond corresponds to a path difference of 300 meters. If the delay of the reflected signal relative to the direct signal measured at a certain sampling point is 3.5 microseconds, this means that the reflected path is 1050 meters longer than the direct path. Based on this path difference, combined with the known coordinates of the sampling point, it can be determined that the communication node must be located on a specific hyperbola with the sampling point and the reflection point as its foci.

[0033] In one embodiment, the node location range can be further narrowed by measuring data from multiple sampling points. When different delay values ​​are measured at three sampling points at different locations, each sampling point can determine a hyperbolic trajectory, and the intersection of the three hyperbolas is the exact location of the interfered communication node. Even taking into account the existence of measurement errors, the intersection area of ​​these hyperbolas can provide a reliable node location interval, which is usually within the range of 50-100 meters, sufficient to meet the needs of subsequent network optimization and interference elimination. This positioning method based on multipath delay makes full use of the reflection phenomenon caused by the complex terrain of the mountainous area, and transforms the original interference factors into favorable conditions for positioning.

[0034] S103, obtaining the terrain shielding degree and signal strength attenuation of the location interval of the interfered communication node, identifying the main signal propagation interference source according to the terrain shielding degree, and determining the dynamic interference weight factor according to the distance between nodes and the terrain complexity.

[0035] For the location interval of the interfered communication node, extract the terrain elevation sampling points at every preset distance in the interval, calculate the difference between the node location elevation and the elevation of each sampling point, and count the proportion of the number of sampling points with positive elevation difference to the total number of sampling points as the terrain shielding degree coefficient. At the same time, measure the actual received signal strength in the interval and compare it with the theoretical signal strength calculated based on the transmission power and propagation distance. The difference between the measurement and the contour is the signal strength attenuation. According to the terrain shielding degree coefficient and the signal strength attenuation, the space around the node is divided into multiple sectors according to the orientation. The product value of the shielding degree coefficient and the signal attenuation of each sector is calculated. If the product value of a sector exceeds the preset threshold and is the largest among all sectors, it is determined that the mountain in the direction of the sector is the main signal propagation interference source, and the center orientation of the sector is recorded as the interference source orientation to obtain the interference source orientation distribution data. Based on the azimuth distribution data of the interference source, the straight-line distance between the interfered node and the adjacent communication node is calculated, the terrain elevation sequence is extracted along the node line, the sum of the absolute values ​​of the elevation differences between adjacent points in the elevation sequence is calculated and divided by the sequence length to obtain the terrain complexity index, the inverse of the distance is multiplied by the terrain complexity index, and then divided by the maximum value of the product of all nodes to determine the dynamic interference weight factor with a value range between 0 and 1.

[0036] Specifically, quantitative assessment of terrain obstruction is a key step in understanding communication interference in mountainous areas.

[0037] In one possible implementation, after determining the location range of the affected node, terrain elevation sampling points are set every 20 meters around the node, forming a sampling grid covering a 1-kilometer radius. Assuming the node is located on a mountainside at an altitude of 1,200 meters, 350 of the 500 sampling points extracted have elevations exceeding 1,200 meters. This means that 70% of the surrounding terrain is higher than the node location, resulting in a significant terrain obstruction effect.

[0038] It should be noted that the calculation of theoretical signal strength is based on unobstructed propagation conditions.

[0039] Specifically, when the transmit power is 30dBm and the propagation distance is 3 kilometers, based on the principle of free-space path loss, the theoretical received signal strength should be -79dBm. However, actual measurements show a received signal strength of only -92dBm, a 13dB difference. This difference directly reflects the additional attenuation caused by mountain obstruction and reflections. This comparison method accurately quantifies the actual impact of terrain on signal propagation. The sectorization method allows for more precise interference source location.

[0040] For example, the 360-degree space around the node is divided into 12 sectors every 30 degrees, with each sector representing a possible interference direction. In the northeast sector, the obstruction coefficient reaches 0.8, and the signal attenuation is 15dB. The product of these two factors is 12, significantly higher than the values ​​in other sectors. This indicates that there are major mountains blocking the northeast, acting as the primary source of interference for signal propagation. This sectorized analysis accurately identifies the terrain features that have the greatest impact on communication quality. Quantifying terrain complexity is crucial for assessing the propagation environment.

[0041] In one embodiment, along a line connecting two nodes 5 kilometers apart, an elevation point is extracted every 100 meters, resulting in 50 elevation data points. If the elevation differences between adjacent sampling points are 15 meters, 8 meters, 23 meters, etc., the absolute sum of the elevation differences of all adjacent points is calculated to be 420 meters, which is divided by the number of sampling points (49) to obtain an average elevation change rate of 8.6 meters. This value reflects the undulation of the terrain along the propagation path, with a typical value between 5-15 meters in mountainous areas and less than 2 meters in plain areas. The normalization of the dynamic interference weight factor ensures comparability between different node pairs.

[0042] Optimally, when the inverse distance of a node pair is calculated to be 0.0002 and the terrain complexity index is 8.6, the product of the two is 0.00172. If the maximum value of this product across all node pairs is 0.0025, the normalized weight factor is 0.688. This value, between 0 and 1, comprehensively reflects the impact of both distance and terrain on the degree of interference. Node pairs with closer distances and more complex terrain receive higher weight factors, thus receiving priority in subsequent network optimization.

[0043] S104: Construct a set of candidate data forwarding paths based on the dynamic interference weight factor, perform feasibility assessment and interference intensity ranking, extract alternative paths that meet communication quality requirements, and screen out the path combination with the least signal propagation interference by calculating the path length change rate and node connectivity change rate of the alternative paths to determine the preliminary forwarding path solution.

[0044] Based on the dynamic interference weight factor, all pairs of adjacent nodes in the communication network are traversed, and node pairs with weight factors less than a preset threshold are marked as available links. Starting from the starting node of the data to be transmitted, all reachable paths to the data receiving node are searched. The sequence of nodes and the weight factor sequence of the corresponding links traversed by each path are recorded, and a data forwarding path candidate set containing all possible paths is constructed. For each path in the data forwarding path candidate set, the dynamic interference weight factors of each link segment on the path are accumulated to obtain the path total interference value. The path total interference value is compared with a preset communication quality threshold. Paths with path total interference values ​​below the threshold are retained as feasible paths. Paths are sorted in ascending order of total interference value, and a preset number of paths with the lowest interference values ​​after sorting are selected as the candidate path set. For each path in the set of alternative paths, the ratio of the number of link segments contained in the path to the minimum number of link segments from the starting node to the receiving node is calculated as the path length change rate. The number of adjacent nodes that can still be reached by each relay node in the path after removing the current path is counted, and the ratio of this number to the number of reachable adjacent nodes before removal is calculated. The ratios of all relay nodes are averaged to obtain the node connectivity change rate. The path with the smallest sum of the path length change rate and the node connectivity change rate is selected and determined as the preliminary forwarding path solution.

[0045] Specifically, the dynamic interference weight factor plays a key screening role in constructing the forwarding path.

[0046] In one possible implementation, a weight factor of 0.3 between two adjacent nodes indicates that the link is less affected by terrain interference and is suitable for data forwarding. A weight factor of 0.8, on the other hand, indicates that a link is severely obstructed by mountains or experiences signal attenuation, making it unsuitable for carrying important data. Setting a threshold of 0.5 effectively distinguishes between usable links and links with high interference, laying the foundation for subsequent path search. The path search process embodies a construction approach that works from the local to the global.

[0047] Specifically, starting from node A, where data is sent, we first identify all neighboring nodes connected to A whose weight factors are below a threshold. Let's assume these are nodes B, C, and D. We then continue to expand outward from these three nodes, searching for their available neighboring nodes, and so on recursively until we reach the data receiving node Z. This process may generate multiple paths, such as ABEZ, ACFGZ, and ADHZ. Each path records a complete sequence of nodes and corresponding weight factor sequences.

[0048] It should be noted that the calculation of the total interference value of the path using an accumulation method can fully reflect the communication quality of the entire path.

[0049] For example, if the weight factors of the three links in path ABEZ are 0.2, 0.3, and 0.4, respectively, the total interference value of the path is 0.9. However, although path ACFGZ passes through four links, the weight factors of each link are only 0.1, 0.2, 0.1, and 0.2, resulting in a lower total interference value of 0.6. This cumulative evaluation method ensures that the selected path has good overall communication performance. The path length change rate reflects the additional overhead incurred by choosing a circuitous path.

[0050] In one embodiment, if the shortest path from originating node A to receiving node Z requires only two hops, but the actual selected path ACFGZ requires four hops, the path length change rate is 2.0. The closer this ratio is to 1.0, the closer the path is to the optimal path length and the lower the transmission delay. Evaluating the node connectivity change rate ensures network robustness.

[0051] Preferably, consider relay node C in path ACFGZ. Assuming C originally connects to five adjacent nodes, after removing path AC, C still connects to four nodes, resulting in a connectivity ratio of 0.8. Similarly, the connectivity ratios of F and G are calculated, and the three are averaged to obtain the node connectivity change rate for the entire path. A higher change rate indicates that selecting that path will not significantly impact the connectivity of other nodes in the network. A comprehensive evaluation mechanism ensures the rationality of the final solution. By adding the path length change rate and the node connectivity change rate, a comprehensive score is obtained for each candidate path. Path ABEZ's length change rate of 1.5 plus its connectivity change rate of 0.7 gives a total score of 2.2. While path ACFGZ is longer, its score is 2.0 + 0.9 = 2.9. Selecting the path with the lowest score as the initial forwarding solution achieves a balance between interference avoidance, transmission efficiency, and network stability.

[0052] S105 , obtaining signal time difference data of each path in the preliminary forwarding path solution, and generating an optimized forwarding path set.

[0053] For each path in the preliminary forwarding path plan, a test signal is sent at the path's starting point. The actual time the signal reaches each relay node and the end point is recorded. The propagation time between adjacent nodes is calculated and compared with the theoretical time obtained by dividing the distance between nodes by the speed of electromagnetic wave propagation. The difference between the two is used as the signal time difference data for each link segment. This signal time difference data is monitored in real time, and the time difference values ​​of all link segments on each path are accumulated to obtain the total path delay deviation. If the total path delay deviation exceeds a preset threshold, the link segment with the largest time difference value is selected, and the coordinates of the nodes at both ends of this link segment are obtained. A search is conducted around the midpoint of the line connecting the two nodes for a location with a higher altitude and no mountain obstruction to determine this location as the replacement relay node. The path configuration is updated using this replacement relay node location, and the signal propagation loss of the updated path is remeasured. If the signal strength at the receiving end is below a preset receive sensitivity threshold, the difference between the threshold and the actual receive strength is calculated. The output power of the transmitting node is increased based on this difference. All paths that have completed local adjustments are summarized to obtain the optimized forwarding path set.

[0054] Specifically, the measurement of signal time difference is an important means to evaluate the quality of communication paths in mountainous areas.

[0055] In one possible implementation, the time at which the test signal is transmitted from originating node A is recorded as t0, and the time at which it reaches the first relay node B is t1. The actual propagation time is t1-t0. Based on the straight-line distance of 500 meters between nodes A and B, divided by the propagation speed of electromagnetic waves in air at 300,000 kilometers per second, the theoretical propagation time should be 1.67 microseconds. If the actual measured time is 2.1 microseconds, the time difference is 0.43 microseconds. This discrepancy is primarily due to the multipath effect caused by reflections off the mountain.

[0056] It should be noted that the cumulative effect of the total path delay deviation can accurately reflect the transmission quality of the entire path.

[0057] Specifically, a path consisting of four link segments, ABCDE, has time differences of 0.43, 0.28, 0.52, and 0.31 microseconds, respectively, for a total delay variation of 1.54 microseconds. When the preset threshold is set at 1.2 microseconds, this path clearly exceeds the threshold and requires optimization. By identifying the CD link segment with the maximum time difference of 0.52 microseconds, the problem can be precisely located. The optimal selection of relay node locations directly impacts signal propagation efficiency.

[0058] For example, the original relay node C is located at the bottom of a valley, and D is located on the opposite mountainside, with a significant mountain ridge blocking the way. During a search within a 1-kilometer radius around the midpoint of the line connecting C and D, a mountaintop platform at an altitude of 1,850 meters was discovered. This location has a direct line of sight with both points C and D, with no terrain obstruction. After moving the relay node to this mountaintop location, although the new propagation path slightly increases the physical distance, it avoids the complex reflection path, and the time difference is reduced to less than 0.15 microseconds. Real-time assessment of signal propagation loss ensures the reliability of the communication link.

[0059] In one embodiment, after path adjustment, the total propagation loss from the starting node to the end node is 115dB. Considering a transmit power of 30dBm, the signal strength at the receiving end is only -85dBm. The sensitivity threshold of the receiving device is typically set at -90dBm. While theoretically possible, this only leaves a 5dB margin, potentially leading to communication interruptions in inclement weather. Implementing a power adjustment strategy improves system stability.

[0060] Preferably, to ensure a link margin of 10dB, the received signal strength needs to reach -80dBm, which is 5dB different from the current -85dBm. The target requirements can be achieved by increasing the transmission power of the starting node by 5dB to 35dBm, or by increasing the transmission power of the relay node by 3dB and the node before the terminal by 2dB. This distributed power adjustment method not only meets the communication needs, but also avoids the interference problem caused by excessive power at a single point. The formation of the forwarding path set reflects the optimization idea at the system level. By performing delay testing, node optimization and power adjustment on multiple paths in the preliminary plan one by one, each path in the final path set meets the dual requirements of delay and signal strength. This optimized forwarding path set not only improves the reliability of data transmission, but also provides high-quality candidate solutions for subsequent dynamic routing selection.

[0061] Obtain the coordinates of nodes where the signal time difference exceeds the threshold, analyze the terrain obstruction angle and altitude difference, select alternative locations based on the line-of-sight conditions, measure the degree of terrain reflection interference at the alternative locations, determine the deployment coordinates of the relay nodes, and adjust the power output level of the transmitting node based on the attenuation of the signal intensity reflected from the mountain. Verify the signal propagation quality of the adjusted path and form an optimized path configuration plan including the new relay coordinates and power parameters.

[0062] After obtaining the coordinates of the node whose signal time difference exceeds the threshold, the relative position data of the node and the surrounding mountains are extracted, and the angle between the top of the mountain and the line connecting the node and the horizontal plane is calculated as the terrain shielding angle. The difference between the node altitude and the average altitude of the surrounding terrain is calculated. If the shielding angle is less than the preset angle and the node altitude is higher than the average altitude of the surrounding terrain, a set of alternative position coordinates that meet the direct path conditions are searched around the node. For each position in the set of alternative position coordinates, a test signal is transmitted and the mountain reflection echo is received. The ratio of the reflected signal power to the direct signal power is measured as an indicator of the degree of terrain reflection interference. The position with the smallest reflection interference degree index is selected as the relay node deployment coordinate, and the terrain fluctuation data around the coordinate point is obtained at the same time. Based on the deployment coordinates of the relay nodes and the data on changes in the surrounding terrain, the total attenuation of the signal propagation path from the transmitting node through the relay node to the receiving node is recalculated. The difference between the preset receiving signal strength threshold and the actual receiving strength is used as the required compensation power. The compensation power is allocated to the corresponding transmitting node according to the proportion of the terrain undulation of each section of the path. After adjusting the power output level of each node, the signal strength value and propagation delay value at both ends of the path are measured. The relay node coordinates, the adjusted power parameters of each node, the signal strength value and the delay value are combined to form an optimized path configuration plan.

[0063] Specifically, the calculation of terrain obstruction angle is a key indicator for evaluating communication conditions in mountainous areas.

[0064] In one possible implementation, consider a communication node located on a mountainside at an altitude of 1,500 meters. Two kilometers northeast of the node lies a 2,100-meter peak. By calculating the angle between the peak and the node relative to the horizontal plane, the resulting obstruction angle is 17 degrees. This angle reflects the degree of terrain obstruction to signal propagation; a larger angle indicates greater mountain obstruction. Given a preset acceptable obstruction angle of 15 degrees, the node clearly does not meet the line-of-sight transmission requirement.

[0065] It should be noted that the judgment of altitude difference is crucial for selecting a suitable relay location.

[0066] Specifically, if the average altitude of the terrain within a 1-kilometer radius of a node is 1,450 meters, while the node itself is 1,500 meters above sea level, the node is 50 meters above the surrounding terrain. This positive altitude difference indicates that the node is located relatively high, which facilitates long-distance signal propagation. By searching for alternative locations at higher altitudes, such as ridgelines above 1,800 meters, better line-of-sight conditions can be achieved. Measuring the degree of terrain reflection interference directly influences the final location selection of relay nodes.

[0067] For example, when testing at three candidate locations, the first location received a reflected signal power of -75dBm and a direct signal power of -60dBm, for a ratio of 0.032. The second location had a ratio of 0.1. The third location, located in an open area, had an extremely weak reflected signal, resulting in a ratio of only 0.01. Selecting the third location, with the smallest ratio, as the relay node deployment point minimizes the impact of multipath interference. The acquisition of data on the surrounding terrain fluctuations provides a basis for subsequent power allocation.

[0068] In one embodiment, analysis of terrain data surrounding the relay node revealed that the path from the node to the transmitter passes through two valleys, resulting in dramatic terrain fluctuations, while the path to the receiver is relatively flat. This asymmetric terrain directly affects the distribution of signal attenuation. The power compensation allocation strategy embodies a refined approach to network optimization.

[0069] Optimally, assuming a total compensation power requirement of 9dB, the power is allocated based on the proportion of terrain undulation in each path segment: the path from the transmitter node to the relay node accounts for 70% of the total undulation and receives a 6dB power boost; the relay node itself receives a 2dB power boost; the path from the relay node to the receiver accounts for 30%, with the last hop receiving a 1dB power boost. This allocation method, proportional to terrain complexity, ensures the rational use of power resources. The formation of the optimized path configuration plan marks the completion of the entire optimization process. By integrating the precise coordinates of the relay nodes, the adjusted power levels of each node, the measured end-to-end signal strength values, and the propagation delay data, a complete set of configuration parameters is formed. Tests show that the optimized path signal strength increases from -92dBm to -78dBm, and the propagation delay decreases from 2.1 microseconds to 1.8 microseconds, significantly improving communication quality in mountainous areas. This optimization solution, based on actual terrain characteristics, provides reliable guarantees for the stable operation of communication networks in mountainous areas.

[0070] S106 , real-time monitoring of changes in the distribution of communication nodes in the forwarding path set, continuous monitoring of changing trends in signal propagation interference, determination of signal loss rate data during path execution, and generation of a stable communication transmission channel.

[0071] Monitor the online status of each communication node in the forwarding path set in real time, periodically obtain node location coordinates and working status data, compare the current node distribution with the initial distribution in the optimized path configuration plan, identify changes in node offline or position offset, and record the real-time measurement values ​​of signal strength and delay on each path. Calculate the deviation of the measurement value relative to the measurement value during the optimized configuration as the change trend data of signal propagation interference. Based on the change trend data of signal propagation interference and the change of node distribution, count the total number of data packets sent and the number of confirmation packets received for each path within a fixed time window, and calculate the ratio of unreceived confirmation packets to the total number of sent packets as the signal loss rate. If the signal loss rate of a path exceeds the preset threshold or the key node is offline, select the currently available path with the highest signal strength from the pre-built alternative paths as the alternative path. The alternative path is used to update the current transmission configuration, and a switching instruction containing the new next-hop node address is sent to each node on the path. After receiving the instruction, the node updates the locally stored next-hop forwarding address and transmits subsequent data packets according to the new forwarding address. The signal loss rate and transmission delay of the path after switching are continuously monitored. When the loss rate remains below the threshold and the delay is stable for multiple consecutive monitoring cycles, it is confirmed that a stable communication transmission channel has been obtained.

[0072] Specifically, real-time monitoring mechanisms play a vital role in mountain communication networks.

[0073] In one possible implementation, a heartbeat packet is sent to each communication node every 30 seconds. Upon receiving it, the node immediately returns a response packet containing its GPS coordinates and battery level. If a mountainside node fails to respond due to a device failure caused by heavy rain, it is immediately marked as offline. Meanwhile, another node, while responding normally, displays its coordinates as having shifted 50 meters from its original position. This shift could be caused by a landslide or human movement, directly impacting communication quality along the original path.

[0074] It should be noted that the changing trend of signal propagation interference can indicate potential communication problems.

[0075] Specifically, during the initial network optimization configuration, the signal strength of a particular path was -75dBm and the transmission delay was 1.5 microseconds. These values ​​were recorded as a baseline. During real-time monitoring, the signal strength of this path dropped to -82dBm and the delay increased to 2.1 microseconds. These deteriorating trends in both indicators indicate the presence of new interference sources or environmental changes, such as additional attenuation caused by seasonal vegetation growth. Calculating the signal loss rate provides a quantitative quality assessment metric.

[0076] For example, within a 5-minute monitoring window, a path sent 1,000 data packets, of which 920 received acknowledgements from the receiver, while 80 received no acknowledgements, resulting in a calculated loss rate of 8%. When the preset acceptable loss rate threshold is 5%, the path clearly fails to meet communication quality requirements. This evaluation method based on actual transmission performance is more reliable than relying solely on signal strength. The selection of alternative paths reflects the network's redundancy design.

[0077] In one embodiment, when a problem occurs on the primary path, the system selects from three pre-configured alternative paths: the first alternative path currently has a signal strength of -79dBm, but a relay node it passes through is low on power; the second path has a signal strength of -77dBm, and all nodes are normal; and the third path, while having the strongest signal strength at -73dBm, has a key node offline. After comprehensive consideration, the second path is selected as the alternative. The implementation of path switching requires precise coordination and control.

[0078] Preferably, the switching instruction includes a new forwarding rule: the data originally forwarded from node A to node B now needs to be forwarded to node C. Each node maintains a next-hop address table and updates the table entries immediately after receiving the switching instruction. To avoid data loss during the switching process, the system adopts a build-first-then-break strategy, that is, first establish a connection for the new path, and then stop using the old path after confirming that it is working properly. Confirmation of the stability of the communication channel requires continuous observation and verification. After switching to the new path, the system continues to count the loss rate and delay data once a minute. The channel is considered to have reached a stable state only when the loss rate remains below 3% and the delay fluctuation does not exceed 0.2 microseconds for 10 consecutive monitoring cycles. This strict stability judgment standard ensures the reliability of communication services in complex mountainous environments and provides users with high-quality data transmission guarantees.

[0079] S107 , analyzing the signal time difference variation trend during the path switching process according to the stable communication transmission channel, and determining the switching time interval, signal strength threshold, and node load balancing coefficient for the path switching.

[0080] Based on the stable operation records of the communication transmission channel, the time of each path switching event, the signal propagation time before and after the switch, and the signal strength value are extracted. The difference between the signal propagation time before and after the switch is calculated. The relationship between the difference and the time after the switch is recorded as a time series, and the signal time difference change data and the corresponding signal strength record during the path switching process are obtained. By performing sliding window statistics on the signal time difference change data, the standard deviation of the time difference within a fixed time window is calculated. When the standard deviation is lower than the preset value for multiple consecutive windows, it is determined to be a stable state. The time from the start of the switch to the stable state is calculated as the switch recovery time. The average recovery time of multiple switches is determined as the switching time interval of the path switch. At the same time, the strength value when the switch is triggered is extracted from the signal strength record, and the median is taken as the signal strength threshold. Based on the switching time interval and signal strength threshold, the number of data packets forwarded by each node in each switching time interval is counted, and the ratio of the forwarding amount of a single node to the average forwarding amount of all nodes is calculated. This ratio is defined as the node load balancing coefficient. The three parameters of the switching time interval, signal strength threshold, and node load balancing coefficient are determined.

[0081] Specifically, the change in time difference during the path switching process reflects the dynamic process of the network adapting to the new path.

[0082] In one possible implementation, when the system performs a path switch at 10:00 AM, the signal propagation time before the switch is 1.8 microseconds. At the moment of the switch, the propagation time suddenly increases to 2.5 microseconds due to the need for nodes to update routing tables and establish new connections. Over the following 30 seconds, this time difference gradually decreases, from 0.7 microseconds to 0.3 microseconds, and finally stabilizes within 0.1 microseconds after 45 seconds. The curve of this time difference exhibits a typical exponential decay characteristic, and recording this data provides a basis for subsequent parameter determination.

[0083] It should be noted that the sliding window statistical method can effectively identify the stable state of the system.

[0084] Specifically, a window length of 5 seconds is set, sliding once per second, and the standard deviation of the time difference values ​​within the window is calculated. In the early stages of path switching, the standard deviation may reach 0.15 microseconds, indicating that the system is in a period of drastic adjustment. When the standard deviation of three consecutive windows is less than 0.05 microseconds, the system is determined to have entered a stable state. By analyzing multiple switching events, it was found that the recovery time is distributed between 40 and 60 seconds. The average value of 50 seconds is taken as the switching time interval, which means that the system needs to wait at least 50 seconds before executing the next switch. The determination of the signal strength threshold requires comprehensive consideration of the rationality of the trigger conditions.

[0085] For example, we collected trigger data from 20 path switching events and found that the signal strengths at the time of the switchovers varied, including -88dBm, -85dBm, and -91dBm. After sorting these values, we took the median, -87dBm, as the signal strength threshold. The median was chosen over the average because it is insensitive to extreme values ​​and better reflects typical trigger conditions, avoiding thresholds that are set too high or too low due to individual anomalies. The calculation of the node load balancing coefficient reveals the distribution characteristics of network traffic.

[0086] In one embodiment, within a 50-second handover interval, node A forwarded 1200 packets, node B forwarded 800, and node C forwarded 1000, for an average forwarding volume of 1000 packets across the three nodes. The calculated load balancing coefficient for node A is 1.2, indicating that it carries 20% more traffic than the average level; node B's coefficient is 0.8, indicating a light load. These coefficients directly reflect the load pressure on each node and provide a quantitative basis for subsequent traffic scheduling.

[0087] Optimally, the determination of these three parameters forms a complete environmental adaptation mechanism. The switching interval ensures that the system has sufficient time to complete the stabilization process after the previous switching, avoiding the oscillation caused by frequent switching. The signal strength threshold provides a clear switching trigger condition, neither premature switching causing waste of resources nor delayed switching affecting communication quality. The node load balancing coefficient supports more refined traffic distribution decisions. This combination of parameters, derived from statistical analysis of historical data, enables mountain communication networks to better adapt to complex and changing environmental conditions, significantly improving network stability and reliability.

[0088] Collect the fluctuation amplitude and frequency distribution data of the signal time difference during the path switching process, identify the time nodes and attenuation rates of signal strength mutations, count the uneven distribution of node loads during the switching period, set the lower limit of the intensity triggering the switching according to the signal strength attenuation rate, determine the target time interval for path switching based on the time difference fluctuation frequency, and determine the load distribution weight coefficient of each node according to the degree of load uneven distribution, and establish a corresponding relationship table between switching parameters and environmental changes.

[0089] The signal strength data series for each switching node during the path switching process is collected, and the time difference between adjacent sampling points is calculated. The frequency domain distribution characteristics of the time difference are obtained through Fourier transform. The main fluctuation frequency components are identified based on the spectral density. The timestamps at which the signal strength drop rate exceeds a preset threshold are recorded as the mutation time nodes, and the average attenuation rate before and after the mutation is calculated. Real-time load data for each node during the switching process is obtained, and the ratio of the load standard deviation to the average load is calculated as the imbalance indicator. If the imbalance exceeds the preset imbalance threshold, the load redistribution process is initiated. The initial distribution weight is determined based on the difference between the current load and the average load of each node. The weight is adjusted by multiplying the attenuation rate and the initial weight to obtain the load distribution weight coefficient for each node. Based on the statistical distribution of the average attenuation rate, the attenuation rate corresponding to the preset quantile is selected as the reference value. The time required for the signal strength to drop to the receiver sensitivity is calculated by dividing the signal strength by the attenuation rate. A preset time margin is added to this time as the strength lower limit for triggering the switching. The target interval for path switching is determined based on the periodic characteristics of the main fluctuation frequency components. Establish a mapping relationship between environmental parameters and switching parameters, record the mutation time node distribution, load distribution weight coefficient and switching trigger intensity lower limit under different temperatures, humidity and electromagnetic interference intensities, divide the environment into segments according to the numerical range of the environmental parameters, and determine the corresponding switching intensity lower limit, target time interval and load distribution weight coefficient combination for each environmental parameter interval to form a corresponding relationship table between environmental changes and switching parameters.

[0090] Specifically, during the path switching process of a wireless communication network, the collection of signal strength data sequences forms the basis of the entire switching decision.

[0091] Specifically, the system uses signal receivers deployed at each switching node to acquire signal strength values ​​at a fixed sampling frequency. The time differences between these sampling points reflect the dynamic nature of the network environment. Converting these time differences from the time domain to the frequency domain through Fourier transform can reveal the periodic fluctuation patterns hidden in the time series.

[0092] It's important to note that spectral density analysis can identify dominant fluctuating frequency components. When the energy of a particular frequency component is significantly higher than that of other frequencies, it indicates that the system exhibits regular signal variations at that frequency. Identifying this dominant fluctuating frequency component provides important insight for determining the interval between path switching. Furthermore, by setting a threshold for the rate of signal strength drop, the system can accurately identify the timing of sudden signal changes, which often indicate a sharp deterioration in the communication environment.

[0093] In one possible implementation, load distribution imbalance is quantified as the ratio of the standard deviation to the mean. This metric intuitively reflects the degree of disparity in the traffic carried by each node. When the imbalance exceeds a preset threshold, it indicates that some nodes may be overloaded while others are idle. Initiating a load redistribution process at this time can effectively improve overall network performance. The weight adjustment process comprehensively considers the impact of signal attenuation rate. Nodes with higher attenuation rates receive smaller weight coefficients, thereby reducing the traffic they carry and avoiding service interruptions caused by signal quality degradation.

[0094] For example, a statistical method is used to determine the lower limit of the handover trigger strength. By analyzing the distribution of attenuation rates in historical data, the attenuation rate corresponding to a specific quantile is selected as a typical value. Based on this typical attenuation rate, the time required for the signal strength to drop from the current strength to the receiving sensitivity is calculated, and an appropriate time margin is added to this value. This method ensures the timeliness of handover while avoiding the system overhead caused by overly frequent handovers. During the process of establishing the mapping relationship between environmental parameters and handover parameters, the system records network performance under different environmental conditions. Temperature changes affect the operating status and signal propagation characteristics of the device, humidity causes changes in signal attenuation, and electromagnetic interference intensity directly affects signal quality. By segmenting the environmental parameters, each interval corresponds to a set of optimized handover parameter configurations. The establishment of this mapping table enables the system to adaptively adjust the handover strategy based on the current environmental conditions, significantly improving the stability and reliability of the network in complex environments.

[0095] The present invention provides a multi-directional communication data forwarding system, which mainly includes: a terrain data acquisition module, which is used to obtain terrain elevation data and mountain surface reflection characteristics, build a three-dimensional terrain simulation environment, calculate the initial visible range between each communication node, and obtain a preliminary signal propagation interference distribution map; an interference area identification module, which is used to identify the area with discontinuity in the visible range according to the preliminary signal propagation interference distribution map, collect the reflected signal and scattered signal in the area with discontinuity in the visible range, and determine the position interval of the interfered communication node according to the signal time difference; an interference source analysis module, which is used to obtain the terrain shielding degree and signal strength attenuation of the position interval of the interfered communication node, identify the main signal propagation interference source according to the terrain shielding degree, and determine the dynamic interference weight factor according to the distance between nodes and the terrain complexity; a path candidate set construction module, which is used to construct a data forwarding system according to the dynamic interference weight factor A set of candidate paths is generated, and a feasibility assessment and interference intensity ranking are performed to extract alternative paths that meet the communication quality requirements. By calculating the path length change rate and node connectivity change rate of the alternative paths, the path combination with the least signal propagation interference is screened out to determine the preliminary forwarding path solution; a path optimization module is used to obtain the signal time difference data of each path in the preliminary forwarding path solution and generate an optimized forwarding path set; a communication monitoring module is used to monitor the distribution changes of communication nodes in the forwarding path set in real time, continuously monitor the changing trend of signal propagation interference, determine the signal loss rate data during the path execution process, and generate a stable communication transmission channel; a channel stability analysis module is used to analyze the signal time difference changing trend during the path switching process based on the stable communication transmission channel, and determine the switching time interval, signal strength threshold and node load balancing coefficient of the path switching. Obviously, those skilled in the art can make various changes and modifications to the embodiments of the present application without departing from the spirit and scope of the embodiments of the present application. Thus, if these modifications and variations of the embodiments of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these changes and variations.

Claims

1. A multi-directional communication data forwarding method, characterized in that: The method comprises: Obtain terrain elevation data and mountain surface reflection characteristics, build a three-dimensional terrain simulation environment, calculate the initial visible range between each communication node, and obtain a preliminary signal propagation interference distribution map; based on the preliminary signal propagation interference distribution map, identify areas with discontinuous visible ranges, collect reflected signals and scattered signals in areas with discontinuous visible ranges, and determine the location interval of the interfered communication nodes based on the signal time difference; obtain the terrain obstruction degree and signal strength attenuation of the location interval of the interfered communication nodes, identify the main signal propagation interference source based on the terrain obstruction degree, and determine the dynamic interference weight factor based on the distance between nodes and the complexity of the terrain; construct a candidate set of data forwarding paths based on the dynamic interference weight factor, and conduct feasibility assessment and interference intensity evaluation. Sorting, extracting alternative paths that meet the communication quality requirements, screening out the path combination with the least signal propagation interference by calculating the path length change rate and node connectivity change rate of the alternative paths, and determining the preliminary forwarding path plan; obtaining the signal time difference data of each path in the preliminary forwarding path plan, and generating an optimized forwarding path set; real-time monitoring of the changes in the communication node distribution of the forwarding path set, continuously monitoring the changing trend of signal propagation interference, determining the signal loss rate data during the path execution process, and generating a stable communication transmission channel; based on the stable communication transmission channel, analyzing the changing trend of the signal time difference during the path switching process, and determining the switching time interval, signal strength threshold, and node load balancing coefficient for path switching.

2. A multi-directional communication data forwarding method according to claim 1, characterized in that: The acquisition of terrain elevation data and mountain surface reflection characteristics, construction of a three-dimensional terrain simulation environment, calculation of the initial visibility range between each communication node, and obtaining a preliminary signal propagation interference distribution map include: By scanning, point cloud data of mountain terrain is acquired, a digital elevation matrix is ​​generated, the altitude value of each grid cell is recorded, the material information of the mountain surface is collected, the electromagnetic wave reflection coefficient of each grid cell is determined, and a three-dimensional terrain database containing elevation information and electromagnetic wave reflection coefficient is constructed; based on the latitude and longitude coordinates and elevation information of the distribution location of the communication nodes, the spatial position of each node is located in the three-dimensional terrain database, the terrain elevation profile data on the node connection path is extracted, and an initial visible node set of each node is generated; based on the distance and transmission power between the nodes in the initial visible node set, the free space propagation loss is calculated, and the electromagnetic wave propagation path is tracked in combination with the electromagnetic wave reflection coefficient, the reflected wave intensity is calculated, the direct signal intensity and the reflected signal intensity are superimposed to generate a composite signal strength value for each node; based on the composite signal strength value, a preliminary signal propagation interference distribution map covering the entire mountain area is generated through spatial interpolation operation.

3. A multi-directional communication data forwarding method according to claim 1, characterized in that: The method of identifying areas with discontinuous visibility ranges based on a preliminary signal propagation interference distribution map, collecting reflected signals and scattered signals from the areas with discontinuous visibility ranges, and determining the location interval of the interfered communication nodes based on signal time differences includes: According to the preliminary signal propagation interference distribution map, the signal strength values ​​of adjacent grid cells are scanned, the discontinuity points where the signal strength difference exceeds the threshold are marked, the continuous discontinuity points are connected to form a discontinuity boundary line, and a set of geographic coordinates of the discontinuity area in the visible range is generated; sampling points are selected from the geographic coordinate set, signals from communication nodes are received, the amplitude variation sequence of the signals from the communication nodes is recorded over time, the arrival times of the direct signal, the reflected signal and the scattered signal are detected, the time difference between the reflected signal and the direct signal and the time difference between the scattered signal and the direct signal are calculated, and a multipath time delay difference table is generated; according to the multipath time delay difference table, combined with the electromagnetic wave propagation speed and terrain elevation data, the surface position coordinates of the reflecting mountain are determined by the positioning principle, the signal transmission path is traced back, and the position interval of the interfered communication node is determined.

4. A multi-directional communication data forwarding method according to claim 1, characterized in that: The obtaining of the terrain shielding degree and signal strength attenuation of the location interval of the interfered communication node and identifying the main signal propagation interference source according to the terrain shielding degree includes: Extract terrain elevation sampling points within the interfered communication node location interval, calculate the difference between the node location elevation and the sampling point elevation, and count the proportion of sampling points with positive elevation difference as the terrain blocking degree coefficient; measure the actual received signal strength in the interfered communication node location interval, compare it with the theoretical signal strength, and generate the signal strength attenuation; divide the space around the node into multiple sectors according to the terrain blocking degree coefficient and the signal strength attenuation, calculate the product value of the blocking degree coefficient and the signal strength attenuation of each sector, select the sector with the largest product value, determine the mountain in the direction of the sector as the main signal propagation interference source, and generate the interference source azimuth distribution data.

5. The multi-directional communication data forwarding method according to claim 1, characterized in that: The method of constructing a data forwarding path candidate set based on the dynamic interference weight factor, performing feasibility evaluation and interference intensity sorting, and extracting candidate paths that meet communication quality requirements includes: According to the dynamic interference weight factor, adjacent node pairs in the communication network are traversed, and node pairs with weight factors lower than a threshold are marked as available links. All reachable paths from the starting node to the receiving node are searched, and the path node sequence and link weight factor sequence are recorded to generate a data forwarding path candidate set; according to the data forwarding path candidate set, the link weight factor of each path is accumulated to generate a total path interference value, and the paths with total interference values ​​lower than the threshold are retained as feasible paths. The paths are sorted according to the total interference value, and the paths with the smallest interference value are selected as the alternative path set.

6. A multi-directional communication data forwarding method according to claim 5, characterized in that: After selecting the path with the smallest interference value as the candidate path set, the method includes: For each path in the alternative path set, the ratio of the number of link segments contained in the path to the minimum number of link segments is calculated to generate a path length change rate; the number of adjacent nodes that each relay node in the alternative path set can reach after the path is removed is counted, and the ratio of this number to the number before removal is calculated to generate a node connectivity change rate; based on the sum of the path length change rate and the node connectivity change rate, the path with the smallest sum is selected to generate a path combination with minimal signal propagation interference.

7. A multi-directional communication data forwarding method according to claim 1, characterized in that: Generating the optimized forwarding path set includes: For each path in the forwarding path plan, a test signal is sent, the time when the signal arrives at each relay node and the end point is recorded, the difference between the propagation time between adjacent nodes and the theoretical time is calculated, and signal time difference data is generated; based on the signal time difference data, the time difference values ​​of all link segments on the path are accumulated to generate the total path delay deviation, and a search is conducted around the midpoint of the link segment with the largest time difference value for a location with a higher altitude and no obstruction to generate a replacement relay node position; based on the replacement relay node position, the path configuration is updated, the signal propagation loss is measured, the transmitting node power is adjusted, and an optimized forwarding path set is generated.

8. A multi-directional communication data forwarding method according to claim 1, characterized in that: The real-time monitoring of the distribution changes of communication nodes in the forwarding path set, the continuous monitoring of the changing trend of signal propagation interference, the determination of the signal loss rate data during the path execution process, and the generation of a stable communication transmission channel include: Real-time monitoring of the online status and location coordinates of each node in the optimized forwarding path set, recording changes in node distribution, measuring deviations in signal strength and latency, and generating data on signal propagation interference change trends. Based on the data, the signal loss rate of the path is calculated, and the alternative path with the highest signal strength is selected as the replacement path. Based on the replacement path, the transmission configuration is updated, a new next-hop node address is sent, and a stable communication transmission channel is generated.

9. A multi-directional communication data forwarding method according to claim 1, characterized in that: The method of analyzing the signal time difference change trend during the path switching process based on the stable communication transmission channel and determining the switching time interval, signal strength threshold and node load balancing coefficient of the path switching includes: Extract the moment of the path switching event and the signal propagation time in the stable communication transmission channel, calculate the time difference before and after the switching, and generate signal time difference change data; calculate the time difference standard deviation based on the signal time difference change data, determine the switching recovery time, and generate the switching time interval for the path switching; extract the signal strength value when the switching is triggered, and generate a signal strength threshold; count the number of data packets forwarded by each node, calculate the ratio of the node forwarding amount to the average forwarding amount, and generate a node load balancing coefficient.

10. A multi-directional communication data forwarding system, characterized in that: The system includes: a terrain data acquisition module for acquiring terrain elevation data and mountain surface reflection characteristics, constructing a three-dimensional terrain simulation environment, calculating the initial visible range between each communication node, and obtaining a preliminary signal propagation interference distribution map; an interference area identification module for identifying areas with discontinuous visible ranges based on the preliminary signal propagation interference distribution map, collecting reflected signals and scattered signals in the areas with discontinuous visible ranges, and determining the position interval of the interfered communication node based on the signal time difference; an interference source analysis module for acquiring the terrain shielding degree and signal strength attenuation of the position interval of the interfered communication node, identifying the main signal propagation interference source based on the terrain shielding degree, and determining the dynamic interference weight factor based on the distance between nodes and the terrain complexity; a path candidate set construction module for constructing a data forwarding path candidate set based on the dynamic interference weight factor, and performing Perform feasibility assessment and interference intensity sorting, extract alternative paths that meet communication quality requirements, and screen out the path combination with the least signal propagation interference by calculating the path length change rate and node connectivity change rate of the alternative paths, and determine the preliminary forwarding path plan; the path optimization module is used to obtain the signal time difference data of each path in the preliminary forwarding path plan and generate an optimized forwarding path set; the communication monitoring module is used to monitor the changes in the communication node distribution of the forwarding path set in real time, continuously monitor the changing trend of signal propagation interference, determine the signal loss rate data during the path execution, and generate a stable communication transmission channel; the channel stability analysis module is used to analyze the changing trend of the signal time difference during the path switching process based on the stable communication transmission channel, and determine the switching time interval, signal strength threshold and node load balancing coefficient of the path switching.

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