Network-Assisted UAV Collision Avoidance via AI-ML Servers
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Solution Overview
Problem
Current wireless communication systems face challenges in providing reliable and efficient network-based aviation services for unmanned aerial vehicles (UAVs), particularly in complex and dynamic environments where signal attenuation and collision avoidance are critical issues.
Innovation Solution
The implementation of network-assisted aviation services that leverage existing infrastructure to provide a flexible Detect and Avoid (DAA) solution, utilizing AI-ML-based servers to enhance spatial awareness of UAVs and prevent collisions, while minimizing reliance on remote pilot stations and human pilots.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network-based aviation services are implemented for UAVs, then collision avoidance capability and safety are improved, but system complexity and infrastructure requirements increase
Solution Approach 1:
The patent introduces network entities (such as access points, base stations, or network servers) as intermediaries between UAVs and the aviation service system. These network entities facilitate communication, coordinate flight paths, and provide collision avoidance services, thereby improving reliability while managing complexity through centralized coordination rather than direct peer-to-peer interactions.
Solution Approach 2:
The patent designs the network infrastructure to serve multiple functions: communication relay, flight coordination, collision avoidance, and service discovery. By making the network infrastructure multi-functional, the system improves collision avoidance capability without proportionally increasing complexity, as existing infrastructure components perform multiple roles.
2Device complexity
If existing wireless infrastructure is leveraged for aviation services, then deployment cost and complexity are reduced, but service reliability and dedicated support for UAVs may be compromised
Solution Approach 1:
The patent enables existing wireless network infrastructure (access points, base stations) to serve dual purposes: general wireless communication and dedicated UAV aviation services. This multi-functionality reduces deployment complexity by reusing existing hardware while maintaining reliability through protocol-level optimizations and dedicated service identification mechanisms.
Solution Approach 2:
The patent introduces local quality by enabling selective activation of aviation service features at different network nodes or geographic areas. Not all infrastructure components need to fully support UAV services, allowing the system to maintain reliability in critical areas while using simplified modes in less critical zones, thus balancing reliability with deployment complexity.
3Measurement precision
If AI-ML-based servers are used to enhance spatial awareness, then collision detection accuracy is improved, but computational resources and processing time increase
Solution Approach 1:
The patent segments the computational tasks for spatial awareness and collision detection between different components: edge devices (UAVs, access points) perform local processing and data collection, while centralized AI-ML servers perform complex analysis. This segmentation reduces the computational burden on any single component while maintaining high accuracy through distributed intelligence.
Solution Approach 2:
The patent applies partial action by using AI-ML models that process only the most critical and relevant data for collision avoidance, rather than analyzing all available data. This selective processing maintains measurement precision for safety-critical functions while reducing overall computational resource consumption through model optimization and data filtering.
4Reliability
If signaling protocols are implemented for service discovery, then network support identification is improved, but communication overhead and message processing time increase
Solution Approach 1:
The patent implements preliminary action by having network entities pre-announce their support for aviation services and pre-configure necessary parameters before actual UAV connectivity is established. This allows UAVs to quickly identify supported networks and establish connections without extensive real-time discovery signaling, reducing processing time while maintaining reliable identification.
Solution Approach 2:
The patent merges multiple signaling functions into unified protocol messages that simultaneously convey network capabilities, service availability, and connectivity parameters. By combining multiple information elements into single messages rather than separate exchange sequences, the system improves identification reliability while reducing total signaling overhead and processing time.
Data Source
AI summary
Certain aspects of the present disclosure provide a method for wireless communication at a user equipment (UE), generally including transmitting signaling indicating the UE is associated with an unmanned aerial vehicle (UAV), receiving signaling indicating that a network supports a network-based aviation service, and participating in the network-involved aviation service after receiving the signaling.