UAV Conditional Handover Using Flight-Path Cell Prioritization
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Solution Overview
Problem
Current conditional handover methods for uncrewed aerial vehicles (UAVs) face challenges in preparing for future cell handovers, as they lack efficient mechanisms to prioritize cell measurements and optimize power consumption based on flight path plans, leading to potential disruptions and inefficiencies in network operations.
Innovation Solution
The method involves communicating a flight path plan to the network, which assigns probabilities to potential target cells and configures the UAV to perform relaxed measurements on cells with low access probability, while prioritizing cells with higher probabilities, and deriving a time window for conditional handover based on the time of stay and preceding handover, allowing the UAV to optimize power consumption and measurement procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the UAV performs measurements on all potential target cells with equal priority, then the handover reliability is improved, but the power consumption increases and measurement efficiency decreases
Solution Approach 1:
The patent applies local quality by differentiating measurement priorities for different target cells based on their accessibility probability. High-probability cells receive prioritized measurements with stricter thresholds, while low-probability cells receive relaxed measurements, creating non-uniform measurement quality across different cells to optimize both reliability and power consumption.
Solution Approach 2:
The patent changes measurement parameters dynamically based on cell probability. The measurement threshold parameter is adjusted: stricter thresholds for high-probability cells and relaxed thresholds for low-probability cells. This parameter adaptation allows the system to maintain handover reliability for likely targets while reducing power consumption for unlikely targets.
2Measurement precision
If the UAV performs strict measurements on all target cells, then the measurement precision is improved, but the power consumption increases and handover timing may be delayed
Solution Approach 1:
The patent applies local quality by assigning different measurement precision levels to different cells based on their probability. High-probability cells undergo strict measurements with lower thresholds for precision, while low-probability cells undergo relaxed measurements with higher thresholds, reducing the time and power spent on unlikely handover targets.
Solution Approach 2:
The patent applies partial action by performing strict measurements only on high-probability cells that are likely to be actual handover targets, while performing relaxed or no measurements on low-probability cells. This partial measurement strategy avoids the time loss associated with strictly measuring all cells while maintaining sufficient precision for likely handovers.
3Reliability
If the UAV prepares for all possible future handovers, then the handover reliability is improved, but the device complexity increases
Solution Approach 1:
The patent applies local quality by configuring different levels of handover preparation for different target cells. High-probability cells receive full conditional handover configurations with detailed parameters, while low-probability cells receive simplified or no configurations. This differentiated configuration approach reduces overall system complexity while maintaining reliability for likely handovers.
Solution Approach 2:
The patent extracts and removes unnecessary handover configurations for low-probability cells from the system. By identifying and eliminating configurations for cells with low accessibility probability, the system reduces configuration complexity and processing overhead while retaining essential configurations for high-probability cells that maintain handover reliability.
4Reliability
If the UAV measures all cells with equal priority, then the handover robustness is improved, but the productivity decreases due to inefficient resource usage
Solution Approach 1:
The patent applies local quality by assigning different measurement priorities and resource allocations to different cells based on their probability. High-probability cells receive dedicated measurement resources and stricter evaluation criteria, while low-probability cells receive minimal resources. This localized resource allocation improves measurement efficiency by focusing efforts on likely handover targets while maintaining robustness through prioritized monitoring of critical cells.
Data Source
AI summary
There is provided an apparatus comprising means for communicating a travel path plan of the apparatus to a communication network; means for receiving from the communication network information of one or more cells of the communication network associated with priorities of accessing; and means for using the received information for adjusting priorities for measurements towards different cells of the network. There is also provided a method and a computer program product.