5G slice-based low-altitude unmanned system communication control method and industrial gateway

Abstract

The invention relates to the technical field of communication, and discloses a 5G slice-based low-altitude unmanned system communication control method and an industrial gateway, and the method comprises the following steps: S1, creating a special communication slice for a low-altitude unmanned system in a 5G core network, and configuring high priority and predefined service quality parameters; s2, based on the created special communication slice, the data processing capability is sunk to an edge computing node, and the edge computing node is deployed at a geographic position close to the low-altitude unmanned system; and S3, after data processing configuration is completed at the edge computing node, independent communication channels are distributed to each unmanned aerial vehicle in the low-altitude unmanned system by using a multiple access technology and a multiple-input-multiple-output technology of the 5G network. According to the invention, by introducing 5G slices, edge computing nodes, dynamic communication path selection and spectrum resource allocation technologies, low time delay, high transmission rate and efficient resource utilization of the low-altitude unmanned system are realized.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and specifically to a low-altitude unmanned system communication control method and an industrial gateway based on 5G slicing. Background Art

[0002] With the increasing adoption of low-altitude unmanned systems, particularly in agriculture, logistics, and urban air mobility, communication stability and efficiency have become crucial. These unmanned systems often rely on real-time control and data transmission, necessitating an efficient and reliable communication network to support their operations. Traditional communication systems face challenges such as high latency, uneven network load, and signal interference, making it difficult for low-altitude unmanned systems to maintain efficient and stable communications at high speeds or in complex environments.

[0003] Existing wireless communication networks, such as 4G and traditional Wi-Fi, are widely used to meet the communication needs of low-altitude unmanned systems. By employing centralized data processing and conventional wireless access technologies, these systems enable basic signal transmission and data exchange. In these systems, drones communicate with ground stations and other drones via shared spectrum resources, relying on existing network architectures to transmit control signals.

[0004] While existing technologies can provide basic communication services for low-altitude unmanned systems, they still have some shortcomings. First, traditional communication systems use centralized data processing, resulting in high network latency, which is particularly serious for UAV systems that require real-time response. Second, existing communication links and spectrum resource allocation mechanisms mostly rely on static configurations, which makes the system unable to effectively adjust in dynamic environments, leading to signal interference and resource contention. More importantly, existing technologies lack flexible adaptive path selection and resource reconfiguration mechanisms, making them unable to cope with rapidly changing network conditions, resulting in limited system performance. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a low-altitude unmanned system communication control method and industrial gateway based on 5G slicing, which solves the problems of high communication delay, serious spectrum resource contention and inability to flexibly adapt to changes in dynamic network environment in the existing technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A low-altitude unmanned system communication control method based on 5G slicing includes the following steps: S1. Create a dedicated communication slice for the low-altitude unmanned system in the 5G core network and configure high priority and predefined service quality parameters as the basis for supporting the communication needs of the low-altitude unmanned system; S2. Based on the created dedicated communication slice, data processing capabilities are transferred to edge computing nodes, which are deployed in a geographical location close to the low-altitude unmanned system. S3. After the edge computing node completes data processing configuration, it uses the multiple access technology and multiple input multiple output technology of the 5G network to allocate independent communication channels for each drone in the low-altitude unmanned system, forming a high-speed communication link. S4. On the basis of completing the allocation of independent communication channels, implement dynamic communication path selection and spectrum resource allocation, adjust the communication link usage status of each drone in the low-altitude unmanned system, and perform corresponding path switching and resource reconfiguration when the network status changes.

[0007] Preferably, in step S1, creating a dedicated communication slice for the low-altitude unmanned system includes: Allocate a dedicated network slice in the 5G core network for low-altitude unmanned systems; Network slicing sets different bandwidth allocation strategies, latency requirements, and network resource priorities based on the specific communication needs of low-altitude unmanned systems; Based on the communication requirements of low-altitude unmanned systems, set the access control strategy of network slices to ensure the transmission of data streams in the network.

[0008] Preferably, in step S1, configuring high priority and predefined quality of service parameters includes: Configure bandwidth resources B for network slicing slice To at least meet the bandwidth requirements of low-altitude unmanned system communications, the bandwidth should satisfy the following formula: B slice ≥B min +ΔB; Where B slice To configure bandwidth resources for network slicing; B min is the minimum bandwidth requirement; ΔB is the bandwidth increment dynamically adjusted according to the network load; Configure the latency requirement T for network slicing slice , the delay should meet the minimum delay requirement T min : T slice ≤T min ; Where, T slice is the delay requirement; T min Minimum latency requirement; Configure the priority parameters of the network slice to prioritize the transmission of high-priority mission data for low-altitude unmanned systems. The priority level is dynamically adjusted by the core network based on system requirements.

[0009] Preferably, in step S2, sinking the data processing capability to the edge computing node includes: Decentralize the communication processing tasks of low-altitude unmanned systems to edge computing nodes that are closer to the systems to ensure low-latency data processing. Deploy real-time data processing modules on edge computing nodes to process drone status information, flight trajectory, and real-time communication needs; Configure a load balancing mechanism at the edge computing node to cope with load changes in different time periods and flight areas, and adjust the allocation of computing resources according to actual needs.

[0010] Preferably, in step S2, the edge computing node deployment includes: Configure a communication processing module on the edge computing node to meet the wireless communication needs of low-altitude unmanned systems and ensure that data packets can be efficiently forwarded to the 5G network core; Configure the interconnection interface between edge computing nodes and other communication equipment to ensure that data can be transmitted stably in different network environments, especially under the high-speed movement conditions of low-altitude unmanned systems.

[0011] Preferably, in step S3, the multiple access technology and the multiple input multiple output technology include: Using time division multiple access and orthogonal frequency division multiple access technology, time slots and frequency resources are dynamically allocated according to the location and flight speed of the UAV; Use multiple-input multiple-output technology in communication links to increase spatial multiplexing; Based on power control algorithms and interference management strategies, appropriate power is allocated to each UAV to minimize interference and maximize signal quality.

[0012] Preferably, in step S3, allocating independent communication channels to each drone includes: Based on location awareness and interference analysis, independent spectrum resources are allocated to each drone; Frequency reuse technology is used to allocate independent channels to different drones in different time and space domains.

[0013] Preferably, in step S4, the implementation of dynamic communication path selection and spectrum resource allocation includes: Dynamically assess the availability and reliability of communication paths based on real-time network status information, including channel quality, bandwidth utilization, and congestion; Based on the path selection algorithm, the optimal communication path under the current network status is selected. The calculation formula is as follows: P opt =argm P in{L path (P)}; Where, L path (P) is the communication delay of path P, and the path P with the minimum path delay is selected. opt ; argmin is a mathematical operator; P represents the number or identifier of the candidate communication path, indicating an optional communication path; Based on the spectrum resource scheduling algorithm, spectrum is allocated in real time according to network congestion and the mission priority of the drone.

[0014] Preferably, in step S4, performing corresponding path switching and resource reconfiguration includes: When a change in network status or a degradation in the performance of the current path is detected, the path switching mechanism is automatically triggered to switch the communication path to a new optimized path. Reconfigure communication link resources based on the new network status to ensure that the new path and resource allocation meet the communication needs of the low-altitude unmanned system; For path switching and resource reconfiguration, a predictive control strategy is adopted. This strategy uses historical network status data to predict future network changes and make adjustments in advance. The formula is as follows: U opt =argm U in{∑t T =0(|R(t)-R target |)}; Where R(t) is the resource configuration of the current path; R target Configure the target resource; U opt is the optimal control decision; argmin is a mathematical operator; U represents the control decision variable, indicating the selection or allocation decision of resource allocation; T represents the total number of time steps, indicating the time period range of resource allocation.

[0015] The present invention also provides an industrial gateway, comprising: A communication processing module is used to receive communication requests from low-altitude unmanned systems, process the communication requests, and then forward data packets to the 5G network core; A data analysis module, connected to the communication processing module, for performing real-time analysis of the communication data stream of the low-altitude unmanned system, wherein the communication data stream includes the flight status, location information and sensor data of the UAV; a network monitoring and control module, connected to the communication processing module and the data analysis module, respectively, for monitoring the communication status of the low-altitude unmanned system, wherein the communication status includes bandwidth utilization, communication link quality, and network load information; a resource scheduling module, connected to the network monitoring and control module, for performing dynamic adjustment of spectrum resources based on the communication status information; The interface coordination module is connected to the communication processing module and the peripheral device respectively, and is used to coordinate the configuration of data exchange and interface protocols between the industrial gateway and the external system to adapt to the communication needs in various network environments.

[0016] The present invention provides a low-altitude unmanned system communication control method and industrial gateway based on 5G slicing. It has the following beneficial effects: 1. This invention combines a dedicated communication network based on 5G slicing with edge computing nodes, significantly reducing communication latency. Compared to traditional centralized data processing methods, this solves the communication delay problem caused by processing delays in remote central servers, enabling low-altitude unmanned systems to maintain efficient, real-time communication even at high speeds.

[0017] 2. This invention successfully implements independent communication channel allocation for each drone in a low-altitude unmanned system through multiple access and multiple-input, multiple-output (MIMO) technologies, achieving high transmission rates and efficient spectrum utilization. Compared with traditional shared spectrum technologies, this technology avoids spectrum resource contention, improves signal stability, and enhances data transmission reliability.

[0018] 3. This invention utilizes dynamic path selection and spectrum resource allocation strategies to automatically switch paths and adjust resources as network status changes, ensuring communication link stability and prioritized task transmission. Compared to existing technologies that rely on static network paths, this invention provides more flexible network adaptability, addressing the inability of traditional methods to cope with dynamic environmental changes.

[0019] 4. This invention optimizes path switching and resource reconfiguration by introducing an intelligent predictive control algorithm, ensuring uninterrupted communication for low-altitude unmanned systems in complex environments. Compared to traditional methods based on manual intervention or fixed rules, this invention automatically predicts network changes based on historical data, enabling proactive adjustments and enhancing the system's automation and intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 Schematic diagram of the method flow of the present invention; Figure 2 This is the industrial gateway architecture diagram of the present invention. DETAILED DESCRIPTION

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the present specification. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0022] Please see the attached Figure 1 , an embodiment of the present invention provides a low-altitude unmanned system communication control method based on 5G slicing, comprising the following steps: S1. Create a dedicated communication slice for the low-altitude unmanned system in the 5G core network and configure high priority and predefined service quality parameters as the basis for supporting the communication needs of the low-altitude unmanned system; The initialization and configuration of the 5G network core layer is a basic link. Its main function is to provide the prerequisites and resource framework support for subsequent edge deployment, link scheduling and dynamic control.

[0023] Based on this, in order to ensure that the communication scheduling of low-altitude unmanned systems is not interfered with by other business systems and to achieve refined resource control, the present invention, at the initial stage of the process, creates exclusive communication slices on the 5G core network side and sets differentiated management strategies for different types of data streams, thereby achieving logical isolation of resources and hierarchical division of service quality.

[0024] This communication slice is not created based on a common allocation strategy, but rather is customized to meet the unique communication requirements of low-altitude unmanned systems. During the configuration process, not only is the mission data priority considered, but multiple metrics such as bandwidth, latency, and congestion control are also modeled to ensure the system operates within the parameters that meet the mission constraints.

[0025] The communication slice created in the 5G core network is a logically isolated virtual network unit with independent control and user planes. The slice is managed through the network slice management function (NSMF) for lifecycle management and is deployed based on the network function virtualization (NFV) resource pool.

[0026] Generally speaking, the resource division of network slicing involves multi-layer structures such as core network, transmission network and access network, among which the present invention mainly focuses on the QoS parameter configuration of the core network.

[0027] In one possible implementation, the quality of service parameters of the communication slice include core indicators such as bandwidth resources, latency constraints, packet priority, and packet loss rate tolerance. These parameters can be adaptively adjusted based on the system's dynamic task model.

[0028] As an option, the bandwidth resource configuration of the communication slice can be expressed as the following formula: B slice ≥B min +ΔB; Where B slice To configure bandwidth resources for network slicing; B min is the minimum bandwidth requirement; ΔB is the bandwidth increment dynamically adjusted according to the network load.

[0029] As a technical supplement, the system also configures strict delay control constraints for communication slices, which are defined as follows: T slice ≤T min ; Where, T slice is the delay requirement; T min Minimum latency requirement.

[0030] Specifically, for data streams such as control instructions and flight control signaling that have strong real-time requirements.

[0031] In one possible implementation, the priority parameter configuration is dynamically updated in combination with the network slice management module (NSMF) and the policy control function (PCF), with an update period of 1 to 5 seconds to adapt to changes in flight mission frequency.

[0032] To ensure consistent resource scheduling across communication slices in a multi-tasking environment, the system also establishes an access control mechanism. This mechanism uses a network access control list (ACL) to identify and filter access requests, allowing only devices with valid identity tokens to access the communication slice.

[0033] In some embodiments, the system configures different access identifiers for different slices. On the core network side, the access node will guide the data to the corresponding slice path based on the S-NSSAI identifier issued by the terminal.

[0034] In addition, to meet the needs of low-altitude unmanned systems in high-speed movement, the slice configuration also includes mobility enhancement parameters. These parameters are combined with the AMF (Access Management Function) module to achieve context preservation and seamless switching between slices.

[0035] S2. Based on the created dedicated communication slice, data processing capabilities are transferred to edge computing nodes, which are deployed in a geographical location close to the low-altitude unmanned system. Based on the aforementioned creation of dedicated communication slices through the 5G core network and the configuration of service quality parameters, in order to further improve the response efficiency and link stability of communication processing, the present invention introduces a collaborative mechanism for edge computing nodes. Through this mechanism, the system sinks part of the computing processing power from the centralized core network to an edge location deployed near the activity area of ​​the low-altitude unmanned system. This setting facilitates the system to make rapid decisions and adjust resources based on the local network status, which is conducive to the implementation of subsequent functional modules such as multiple access and dynamic path control.

[0036] In this embodiment, based on the created dedicated communication slice, the system starts the edge computing deployment process. The edge computing node (hereinafter referred to as MEC node) is an extension component of the user plane function in the 5G network architecture. Its deployment location is preferably close to the dense flight path area of ​​low-altitude unmanned systems, the air-to-ground conversion intersection area or the temporary mission coverage area.

[0037] Typically, MEC nodes are integrated with access gateways (gNBs) through physical coupling or logical pairing to form an independently operational local service domain. This service domain supports containerized service hosting, and resource scheduling cycles are typically controlled within 20ms-50ms.

[0038] In one possible implementation, the data processing functions undertaken by the MEC node include but are not limited to the following: Data packet parsing of drone upload links; Real-time decoding of flight status signals; Reflection and dynamic mapping of track coordinates; Pre-classification and buffering of raw data such as sensor images and thermal signals; To cope with the changes in task density caused by the fluctuation of the number of drones in different areas, the system configures a load balancing module in the MEC node. This module introduces a load-aware scheduling function L(t) to evaluate the current node load: Where, L(t) represents the system load ratio at time t; C i (t) is the computing resources occupied by the i-th service container; C total is the maximum computing capacity that the current MEC node can provide; n is the number of task containers running in the node.

[0039] When L(t) (the threshold is set to 0.85), the system triggers the lightweight task migration strategy to transfer some non-critical processing traffic to adjacent MEC nodes; if the system detects that the adjacent nodes have insufficient idle resources, it starts the microservice compression scheduling strategy to release redundant computing resources.

[0040] Specifically, to ensure consistency maintenance during task transfer between MEC nodes, the system uses service state mirroring technology to perform periodic state snapshots and parameter synchronization, with a mirroring frequency of no less than 2 times per second.

[0041] As an option, the deployment architecture of edge computing nodes adopts edge grid architecture, which allows multiple MEC nodes to interconnect. In this architecture, the task distribution strategy refers to the delay prediction function T pred (x,y): T pred (x,y)=T base +γ·Dx,y +η; Where, T pred (x,y) represents the predicted delay of migrating the computing task from node x to node y; T base Is the basic communication overhead; D x,y is the physical distance between node x and node y; η is the distance weight coefficient; γ is the system-level network fluctuation interference term.

[0042] During the deployment process, the MEC node supports the establishment of a high-speed data channel with the core network UPF module through the N6 interface to ensure that data can be forwarded synchronously between the edge and core networks.

[0043] In some embodiments, the deployment of the edge node also includes a communication processing module for performing parsing of the wireless communication protocol of the low-altitude unmanned system and adapting the data packet to the internal protocol stack of the 5G network.

[0044] In addition, edge nodes are equipped with interconnection interfaces with other network devices. These interfaces use physical 10G Ethernet channels or virtual logical links based on SDN controllers, and feature an adaptive rate adjustment mechanism. In scenarios where high-speed, dynamic network conditions exist within the flight area, this mechanism dynamically modifies interface parameters via control commands to achieve data link rate matching.

[0045] To achieve regional load flow and computing coordination between edge nodes, the system introduces a control plane agent module to perform synchronous broadcast of task scheduling decisions and establish a task priority queuing table between nodes based on priority and channel occupancy status.

[0046] S3. After the edge computing node completes the data processing configuration, the multiple access technology and multiple input multiple output technology of the 5G network are used to allocate independent communication channels for each drone in the low-altitude unmanned system to form a communication link with a high transmission rate; in the present invention, the deployment and configuration of the edge computing node provides powerful data processing support for the communication of the low-altitude unmanned system. By completing data processing at the edge node close to the drone flight area, the communication delay can be effectively reduced, ensuring that the system can respond to the communication needs of each drone in real time. On this basis, combined with the multiple access technology and multiple input multiple output technology (MIMO) of the 5G network, the present invention realizes the allocation of independent communication channels for each drone in the low-altitude unmanned system, ensuring that the system can support communication links with high transmission rates and low delays.

[0047] After the edge computing nodes complete data processing configuration, the system leverages the 5G network's multiple access technology to dynamically allocate independent time slots and frequency resources to each drone. This technology, which employs time division multiple access (TDMA) and orthogonal frequency division multiple access (OFDMA), dynamically adjusts the allocation of time slots and frequency resources through real-time information exchange between the base station and the drones, ensuring interference-free communication between drones and optimal utilization of network resources.

[0048] Typically, each drone's communication needs are assessed based on its flight speed, altitude, and current network status. Based on this information, the system dynamically adjusts its wireless resource allocation strategy, ensuring smooth communication through multiple access technologies (such as TDMA and OFDMA). Time Division Multiple Access (TDMA) allocates communication resources within different time slots, preventing different drones from occupying the same time slot simultaneously and thus reducing interference. Frequency Division Multiple Access (FDMA) allocates independent frequency resources to each drone, ensuring that frequencies do not conflict with each other and improving spectrum utilization.

[0049] As an option, this embodiment also incorporates Multiple-Input Multiple-Output (MIMO) technology. This technology increases the spatial reuse of wireless channels through multiple transmit and receive antennas, thereby improving signal transmission rates and communication link stability. MIMO technology dynamically adjusts the signal transmission direction and reception mode based on each drone's geographic location and flight path to achieve more efficient data transmission. Specifically, the system utilizes MIMO's spatial diversity characteristics to enhance the signal's anti-interference capability while improving the network's spectral efficiency.

[0050] In one possible implementation, the system dynamically adjusts the transmit power of each drone using a power control algorithm. Based on the distance between the drone and the base station and the current channel quality, the system automatically adjusts the transmit power to reduce signal interference while maximizing signal quality. The power control algorithm can be expressed as the following formula: Where, P i is the transmission power of the i-th UAV; P max is the maximum power of the system; α is the power attenuation factor, which indicates the ratio of signal strength to decrease with increasing distance; is the distance between the i-th UAV and the base station.

[0051] Specifically, the introduction of MIMO technology optimizes the multipath propagation characteristics of signals. By transmitting the same data through different signal paths, the system maximizes spatial resources while avoiding signal interference. The system dynamically adjusts the signal transmission mode based on different flight conditions and geographic locations, ensuring unimpeded communication quality during drone flight.

[0052] As an option, to further enhance communication stability, the system also employs an intelligent interference management strategy. This strategy selectively encrypts signals and suppresses interference based on real-time network load and signal quality information. The system employs an interference management algorithm based on real-time feedback, optimizing signal transmission quality under varying network conditions. The interference management algorithm can be expressed as follows: Where, I total is the total interference power; I i is the interference power of the i-th interference source; n is the number of task containers running in the node.

[0053] In some embodiments, to ensure efficient communication links, the system also employs an adaptive modulation and coding (AMC) scheme. Based on the current channel quality, the system automatically selects the appropriate modulation and coding scheme to balance the transmission rate and bit error rate, further improving the system's communication efficiency.

[0054] S4. On the basis of completing the independent communication channel allocation, implement dynamic communication path selection and spectrum resource allocation, adjust the communication link usage status of each drone in the low-altitude unmanned system, and perform corresponding path switching and resource reconfiguration when the network status changes; After successfully assigning an independent communication channel to each drone, the system further utilizes dynamic communication path selection and spectrum resource allocation technologies to ensure that low-altitude unmanned systems maintain efficient communication performance in varying flight environments. By monitoring network status changes in real time, the system dynamically adjusts the communication link usage of each drone based on key parameters such as bandwidth utilization and channel quality. Furthermore, the system features automatic path switching and resource reconfiguration capabilities, automatically optimizing communication paths in the event of network congestion or link quality degradation, ensuring unimpeded communication between drones.

[0055] In this embodiment, after completing independent communication channel allocation, the system collects and analyzes real-time network status information for low-altitude unmanned systems, including channel quality, bandwidth utilization, signal strength, and network load. Based on this real-time information, the system initiates a dynamic communication path selection algorithm to select the optimal communication path under current network conditions and optimize each communication link based on the path's latency and bandwidth requirements. The system then selects the most appropriate communication path for each drone based on factors such as its communication needs, geographic location, and flight speed.

[0056] In general, the communication path selection is based on the current signal strength, path delay and bandwidth requirements between the drone and the base station, and the optimal path is automatically selected to ensure the stability of the communication link. The path selection formula is as follows: Where, L path (P) is the communication delay of path P, and the path P with the minimum path delay is selected. opt ; argmin is a mathematical operator; P represents the number or identifier of the candidate communication path, indicating an optional communication path.

[0057] Based on the spectrum resource scheduling algorithm, spectrum is allocated in real time according to network congestion and the mission priority of the drone.

[0058] As an option, to further improve system resource utilization and network efficiency, this embodiment also introduces a dynamic spectrum resource allocation mechanism. Under this mechanism, the system dynamically adjusts spectrum resource allocation based on real-time network load and the UAV's communication task priority. Spectrum allocation takes into account factors such as channel quality, interference, the UAV's flight status, and task urgency. When wireless channel resources are sufficient, the system prioritizes communication resources for high-priority tasks. When spectrum resources are scarce, the system reclaims and reallocates resources based on task priority and bandwidth requirements.

[0059] Specifically, the spectrum resource allocation process can be expressed by the following formula: Where R i The spectrum resources allocated to the i-th UAV; B slice is the total bandwidth resource in the network slice; T total is the total bandwidth requirement of all drones in the system; P i is the transmission power of the i-th UAV.

[0060] In one possible implementation, when the system detects a drop in signal quality on a communication link or network congestion, it automatically triggers a path switching mechanism, switching the communication path to a new, optimized path. Simultaneously, the system reconfigures resources on the new communication path to ensure it meets the drone's communication needs. The path switching and resource reconfiguration process is optimized using the following predictive control strategy: Where R(t) is the resource configuration of the current path; R target Configure the target resource; U optis the optimal control decision; argmin is a mathematical operator; U represents the control decision variable, indicating the selection or allocation decision of resource allocation; T represents the total number of time steps, indicating the time period range of resource allocation.

[0061] By combining historical data and real-time network status, this formula can predict future network changes and make path selection and resource adjustments in advance to avoid the impact of network congestion or link quality degradation on communications.

[0062] In some embodiments, to further optimize system responsiveness, path switching and resource reconfiguration also employ a machine learning-based predictive control approach. This approach uses historical network status data to train a predictive model, predicting network status changes in real time and making adjustments in advance, thereby improving system adaptability and flexibility.

[0063] The industrial gateway described below and the low-altitude unmanned system communication control method based on 5G slicing described above can be referenced to each other.

[0064] Please see the attached Figure 2 The present invention also provides an industrial gateway, comprising: A communication processing module is used to receive communication requests from low-altitude unmanned systems, process the communication requests, and then forward data packets to the 5G network core; A data analysis module, connected to the communication processing module, for performing real-time analysis of the communication data stream of the low-altitude unmanned system, wherein the communication data stream includes the flight status, location information and sensor data of the UAV; a network monitoring and control module, connected to the communication processing module and the data analysis module, respectively, for monitoring the communication status of the low-altitude unmanned system, wherein the communication status includes bandwidth utilization, communication link quality, and network load information; a resource scheduling module, connected to the network monitoring and control module, for performing dynamic adjustment of spectrum resources based on the communication status information; The interface coordination module is connected to the communication processing module and the peripheral device respectively, and is used to coordinate the configuration of data exchange and interface protocols between the industrial gateway and the external system to adapt to the communication needs in various network environments.

[0065] The industrial gateway of this embodiment can be used to execute the above method embodiment. Its principles and technical effects are similar and will not be repeated here.

[0066] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A low-altitude unmanned system communication control method based on 5G slicing, characterized in that: The following steps are involved: S1. Create a dedicated communication slice for the low-altitude unmanned system in the 5G core network and configure high priority and predefined service quality parameters as the basis for supporting the communication needs of the low-altitude unmanned system; S2. Based on the created dedicated communication slice, data processing capabilities are transferred to edge computing nodes, which are deployed in a geographical location close to the low-altitude unmanned system. S3. After the edge computing node completes data processing configuration, it uses the multiple access technology and multiple input multiple output technology of the 5G network to allocate independent communication channels for each drone in the low-altitude unmanned system, forming a high-speed communication link. S4. On the basis of completing the allocation of independent communication channels, implement dynamic communication path selection and spectrum resource allocation, adjust the communication link usage status of each drone in the low-altitude unmanned system, and perform corresponding path switching and resource reconfiguration when the network status changes.

2. The low-altitude unmanned system communication control method based on 5G slicing according to claim 1 is characterized in that: In step S1, creating a dedicated communication slice for the low-altitude unmanned system includes: Allocate a dedicated network slice in the 5G core network for low-altitude unmanned systems; Network slicing sets different bandwidth allocation strategies, latency requirements, and network resource priorities based on the specific communication needs of low-altitude unmanned systems; Based on the communication requirements of low-altitude unmanned systems, set the access control strategy of network slices to ensure the transmission of data streams in the network.

3. The communication control method for a low-altitude unmanned system based on 5G slicing according to claim 1, characterized in that: In step S1, configuring high priority and predefined quality of service parameters includes: Configure bandwidth resources B for network slicing slice To at least meet the bandwidth requirements of low-altitude unmanned system communications, the bandwidth should satisfy the following formula: B slice ≥B min +ΔB; Where B slice To configure bandwidth resources for network slicing; B min is the minimum bandwidth requirement; ΔB is the bandwidth increment dynamically adjusted according to the network load; Configure the latency requirement T for network slicing slice , the delay should meet the minimum delay requirement T min : T slice ≤T min ; Where, T slice is the delay requirement; T min Minimum latency requirement; Configure the priority parameters of the network slice to prioritize the transmission of high-priority mission data for low-altitude unmanned systems. The priority level is dynamically adjusted by the core network based on system requirements.

4. The low-altitude unmanned system communication control method based on 5G slicing according to claim 1 is characterized in that: In step S2, sinking the data processing capability to the edge computing node includes: Decentralize the communication processing tasks of low-altitude unmanned systems to edge computing nodes that are closer to the systems to ensure low-latency data processing. Deploy real-time data processing modules on edge computing nodes to process drone status information, flight trajectory, and real-time communication needs; Configure a load balancing mechanism at the edge computing node to cope with load changes in different time periods and flight areas, and adjust the allocation of computing resources according to actual needs.

5. The communication control method for a low-altitude unmanned system based on 5G slicing according to claim 4 is characterized in that: In step S2, the edge computing node deployment includes: Configure a communication processing module on the edge computing node to meet the wireless communication needs of low-altitude unmanned systems and ensure that data packets can be efficiently forwarded to the 5G network core; Configure the interconnection interface between edge computing nodes and other communication equipment to ensure that data can be transmitted stably in different network environments, especially under the high-speed movement conditions of low-altitude unmanned systems.

6. The communication control method for a low-altitude unmanned system based on 5G slicing according to claim 1, characterized in that: In step S3, the multiple access technology and the multiple input multiple output technology include: Using time division multiple access and orthogonal frequency division multiple access technology, time slots and frequency resources are dynamically allocated according to the location and flight speed of the UAV; Use multiple-input multiple-output technology in communication links to increase spatial multiplexing; Based on power control algorithms and interference management strategies, appropriate power is allocated to each UAV to minimize interference and maximize signal quality.

7. The communication control method for a low-altitude unmanned system based on 5G slicing according to claim 1, characterized in that: In step S3, allocating independent communication channels to each UAV includes: Based on location awareness and interference analysis, independent spectrum resources are allocated to each drone; Frequency reuse technology is used to allocate independent channels to different drones in different time and space domains.

8. The communication control method for a low-altitude unmanned system based on 5G slicing according to claim 1, characterized in that: In step S4, the implementation of dynamic communication path selection and spectrum resource allocation includes: Dynamically assess the availability and reliability of communication paths based on real-time network status information, including channel quality, bandwidth utilization, and congestion; Based on the path selection algorithm, the optimal communication path under the current network status is selected. The calculation formula is as follows: P opt =argm P in{L path (P)}; Where, L path (P) is the communication delay of path P, and the path P with the minimum path delay is selected. opt ; argmin is a mathematical operator; P represents the number or identifier of the candidate communication path, indicating an optional communication path; Based on the spectrum resource scheduling algorithm, spectrum is allocated in real time according to network congestion and the mission priority of the drone.

9. The low-altitude unmanned system communication control method based on 5G slicing according to claim 1 is characterized in that: In step S4, performing corresponding path switching and resource reconfiguration includes: When a change in network status or a degradation in the performance of the current path is detected, the path switching mechanism is automatically triggered to switch the communication path to a new optimized path. Reconfigure communication link resources based on the new network status to ensure that the new path and resource allocation meet the communication needs of the low-altitude unmanned system; For path switching and resource reconfiguration, a predictive control strategy is adopted. This strategy uses historical network status data to predict future network changes and make adjustments in advance. The formula is as follows: Where R(t) is the resource configuration of the current path; R target Configure the target resource; U opt is the optimal control decision; argmin is a mathematical operator; U represents the control decision variable, indicating the selection or allocation decision of resource allocation; T represents the total number of time steps, indicating the time period range of resource allocation.

10. An industrial gateway, according to the low-altitude unmanned system communication control method based on 5G slicing according to any one of claims 1-9, characterized in that: include: A communication processing module is used to receive communication requests from low-altitude unmanned systems, process the communication requests, and then forward data packets to the 5G network core; A data analysis module, connected to the communication processing module, for performing real-time analysis of the communication data stream of the low-altitude unmanned system, wherein the communication data stream includes the flight status, location information and sensor data of the UAV; a network monitoring and control module, connected to the communication processing module and the data analysis module, respectively, for monitoring the communication status of the low-altitude unmanned system, wherein the communication status includes bandwidth utilization, communication link quality, and network load information; a resource scheduling module, connected to the network monitoring and control module, for performing dynamic adjustment of spectrum resources based on the communication status information; The interface coordination module is connected to the communication processing module and the peripheral device respectively, and is used to coordinate the configuration of data exchange and interface protocols between the industrial gateway and the external system to adapt to the communication needs in various network environments.

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