UAV Path Optimization for Multicast Energy Efficiency
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Solution Overview
Problem
UAV communication systems face challenges in energy efficiency due to limited multicast transmission rates, which are constrained by the worst channel condition in user groups, leading to frequent communication interruptions when energy levels become insufficient during transmission tasks.
Innovation Solution
A method for path optimization in UAV communication systems involves dividing users into multicast groups, determining optimal hovering positions and flying paths using algorithms like genetic algorithms and SVM models to minimize energy consumption, considering both mechanical and communication energy, and iteratively optimizing these positions to achieve the lowest total energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional wireless multicast techniques are used, then the same data can be transmitted to multiple users simultaneously, but the multicast transmission rate is limited by the user with the worst channel condition
Solution Approach 1:
The patent segments users into multiple groups based on channel conditions, allowing different transmission rates for different groups. This resolves the contradiction by enabling faster transmission to users with good channel conditions while maintaining reliability for users with poor conditions through separate group management.
Solution Approach 2:
The patent dynamically adjusts transmission parameters and group assignments based on real-time channel conditions. This allows the system to adapt transmission rates to current channel states, improving overall multicast transmission rate while maintaining reliability for each user group.
2Reliability
If a UAV hovers at a fixed position to serve users, then communication stability is improved, but energy consumption increases due to prolonged hovering
Solution Approach 1:
The patent implements dynamic hovering position optimization where the UAV adjusts its hovering position and serving user groups based on real-time energy consumption and channel conditions. This resolves the contradiction by maintaining communication stability through controlled hovering while reducing energy consumption through optimized position selection and dynamic group reassignment.
Solution Approach 2:
The patent employs periodic optimization cycles where the UAV evaluates energy consumption and channel conditions at intervals, adjusting hovering positions and user groups periodically. This maintains communication stability during hovering periods while reducing overall energy consumption through strategic position changes.
3Device complexity
If the UAV serves all users in a single multicast group, then transmission coordination is simplified, but the transmission time and energy consumption increase
Solution Approach 1:
The patent segments users into multiple multicast groups with different transmission rates based on channel conditions. This resolves the contradiction by reducing overall transmission time through parallel transmission to multiple groups while managing complexity through automated group assignment algorithms that match users to appropriate groups based on their channel characteristics.
Data Source
AI summary
Disclosed is a method of path optimization for an unmanned aerial vehicle (UAV). In the method, users and the positions of the users are obtained; the users are divided into K wireless multicast user groups; K initial hovering positions corresponding to the K wireless multicast user groups are determined; and a first shortest flying path connecting the K initial hovering positions is determined; and the initial hovering positions of the UAV are optimized to obtain K final hovering positions and a final flying path. The present disclosure also discloses a device of path optimization for a UAV and a computer readable storage medium.