Real-Time UAV Carrier Selection for Bandwidth and Interference
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Solution Overview
Problem
Existing communication networks are not optimized for the diverse connectivity requirements of unmanned aerial vehicles (UAVs), which vary based on flight missions such as video streaming or parcel delivery, leading to inefficiencies in bandwidth, interference, and operational constraints.
Innovation Solution
Implementing a closed-loop feedback and control mechanism, known as a 'drone service', that utilizes network state information and machine learning to manage UAV operations, including selecting optimal carrier frequencies and flight paths to optimize energy consumption, throughput, and mitigate interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing communication networks are used for UAVs with diverse connectivity requirements, then basic communication functionality is maintained, but bandwidth efficiency deteriorates and interference increases
Solution Approach 1:
The patent dynamically changes communication parameters including carrier frequency selection, bandwidth allocation, and power levels based on real-time network state and UAV mission requirements. The network controller adjusts these parameters to optimize bandwidth efficiency while minimizing interference with other users and UAVs.
Solution Approach 2:
The system implements dynamic carrier selection where the carrier frequency and bandwidth allocated to each UAV are not fixed but change in real-time based on network conditions, mission requirements, and interference levels. This dynamic adaptation allows the network to efficiently serve diverse UAV applications from video streaming to parcel delivery.
2Productivity
If network state information is continuously monitored and processed, then communication efficiency is improved, but system complexity increases
Solution Approach 1:
The patent introduces a network controller as an intermediary that centralizes the complex tasks of monitoring network state information, processing data about multiple UAVs, and making carrier selection decisions. This mediator absorbs the computational complexity, allowing individual UAVs to operate with simpler local logic while achieving optimized communication through centralized coordination.
Solution Approach 2:
The system implements closed-loop feedback where the network controller continuously monitors network state information including channel conditions, interference levels, and UAV performance metrics. This feedback is processed to dynamically adjust carrier frequency assignments and bandwidth allocation, improving communication efficiency through data-driven decisions while managing complexity through iterative optimization.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, a drone service retrieving network state information describing a network state of at least a portion of a communication network, determining an impact of the network state on operation of an unmanned aerial vehicle (UAV), selecting a carrier frequency to be used for communication by the UAV, and providing the data describing the carrier frequency to the UAV and/or to communication network nodes. Other embodiments are disclosed.