3D UAV Network Coverage Computation for Air Traffic Guidance
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Solution Overview
Problem
Current radio network planning techniques are inadequate for managing unmanned aerial vehicle (UAV) traffic beyond visual line of sight, as they lack three-dimensional coverage analysis and real-time network data, which are critical for ensuring safety and connectivity in dynamic air traffic environments.
Innovation Solution
An apparatus and method that compute three-dimensional (3D) network coverage data by correlating stored network data with current connectivity data, including handover probabilities and interference, to facilitate safe and efficient UAV guidance, and automatically report this data to aviation control nodes for real-time air traffic control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current radio network planning techniques are used for UAV traffic management, then device complexity is reduced, but measurement precision and reliability of 3D coverage data are insufficient
Solution Approach 1:
The patent transitions from traditional 2D radio network planning to 3D coverage analysis by incorporating altitude information and vertical dimension parameters. This enables accurate representation of UAV connectivity in three-dimensional space, resolving the insufficiency of conventional 2D techniques for 3D flight environments.
Solution Approach 2:
The system integrates multiple data sources including stored network data, current connectivity data, and 3D coverage data into a unified framework. This multi-functional approach allows the same system to handle both traditional 2D ground network planning and 3D aerial UAV traffic management, reducing overall system complexity while improving measurement precision.
2Reliability
If real-time 3D network coverage data is computed and reported, then reliability and safety of UAV operation are improved, but loss of time and productivity increase due to data processing
Solution Approach 1:
The system pre-computes and stores network coverage data in three dimensions before UAV operations begin. This preliminary action allows real-time queries during flight to simply retrieve pre-calculated coverage information rather than performing complex computations, thereby maintaining high reliability while minimizing time loss.
Solution Approach 2:
The patent replaces traditional mechanical real-time computation with an information-based retrieval system. By pre-calculating and storing 3D coverage data, the system substitutes complex real-time mathematical computations with faster data lookup and correlation operations, reducing processing time while maintaining safety and reliability.
3Reliability
If handover probability and interference data are included in 3D coverage data, then reliability of network connection is improved, but device complexity and data processing requirements increase
Solution Approach 1:
The system calculates handover probability and interference data specifically for relevant 3D locations and scenarios rather than uniformly across all possible configurations. This localized approach focuses computational resources on critical areas where connection stability is most challenging, improving reliability without proportionally increasing overall system complexity.
Solution Approach 2:
The patent introduces an intermediary processing layer that correlates stored network data with current connectivity data to derive handover probability and interference metrics. This intermediary layer abstracts the complexity of calculating these parameters, presenting simplified reliable data to the UAV guidance system while handling the complex computations internally.
4Productivity
If prompt adaptation of flight paths to changing network conditions is enabled, then productivity and efficiency of UAV operation are improved, but measurement precision requirements and device complexity increase
Solution Approach 1:
The system implements continuous feedback loops where current connectivity data is constantly monitored and correlated with stored 3D coverage data. This feedback mechanism enables real-time detection of network condition changes and automatic flight path adjustments, improving productivity while maintaining manageable measurement precision requirements through iterative refinement.
Solution Approach 2:
The patent enables dynamic flight path adaptation by making the UAV guidance system responsive to changing network conditions. Rather than static pre-planned paths, the system continuously adjusts flight parameters based on real-time 3D coverage data, handover probabilities, and interference levels, thereby improving operational efficiency without requiring excessive measurement precision at any single moment.
Data Source
AI summary
The present disclosure provides an apparatus and a method for computing data for guiding unmanned aerial vehicles (UAVs) in a three-dimensional (3D) air space. Stored network data including location data of network nodes as well as current network data including current connectivity data of the network nodes are acquired. By correlating the stored and current network data, current 3D coverage data indicating current network coverage along three dimensions in the 3D flight area (e.g. a handover probability or an interference caused by a UAV) are determined. The techniques of the present disclosure enable modeling and predicting a current coverage and connectivity state of 3D air space and facilitates control and operation of UAV air traffic.