UAV Base Station Trajectory Planning via Tree Search Optimization
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Solution Overview
Problem
Current methods for UAV base station trajectory planning and resource management are inefficient due to high computational complexity, limited battery capacity, inability to update trajectories optimally, incorrect user association, and failure to account for varying user demand, leading to suboptimal communication services.
Innovation Solution
A tree-search based method that decomposes the optimization problem into sub-problems using a time axis, employing depth-first search and Lagrangian dual problems to optimize trajectory planning, user association, resource allocation, and power control, while considering quality-of-service constraints and user demand.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If matching game and convex optimization solver are used to optimize trajectory and resource allocation, then optimality of solution is improved, but computational complexity increases significantly
Solution Approach 1:
The patent segments the complex joint optimization problem into separate sub-problems: trajectory optimization using tree search algorithm and resource allocation using convex optimization. This segmentation allows each sub-problem to be solved independently with appropriate algorithms, reducing overall computational complexity while maintaining solution quality.
Solution Approach 2:
The patent extracts the trajectory optimization component from the joint optimization problem and handles it separately using tree search algorithm. This extraction removes the combinatorial complexity from the resource allocation problem, allowing convex optimization to focus only on continuous variables.
2Measurement precision
If convex optimization solver is used for trajectory optimization, then solution accuracy is improved, but computation time increases when many users are served
Solution Approach 1:
The patent replaces the conventional convex optimization solver for trajectory optimization with a tree search algorithm. This substitution uses a different computational approach that is more efficient for the specific structure of the trajectory optimization problem, reducing computation time while maintaining accuracy.
3Ease of manufacture
If weighted sum-rate maximization is used as optimization objective, then mathematical tractability is improved, but proportional fairness deteriorates
Solution Approach 1:
The patent changes the optimization objective from weighted sum-rate maximization to proportional fairness maximization. This parameter change in the objective function maintains mathematical tractability through the tree search approach while directly achieving the desired fairness property in the solution.
Data Source
AI summary
The present disclosure relates to a tree-search based trajectory planning and resource management method and apparatus of an unmanned aerial vehicle base station. The tree-search based trajectory planning and resource management method of an unmanned aerial vehicle base station according to an embodiment of the present disclosure includes: decomposing an optimization problem of trajectory planning, user association (UA), resource allocation (RA), and power control (PC) related to the unmanned aerial vehicle base station into a time axis; managing resources by jointly optimizing variables of the UA, RA, and PC for an arbitrary location of the unmanned aerial vehicle base station; and obtaining the trajectory planning by obtaining position variables based on the obtained predetermined function value and a depth-first search (DFS) algorithm.