UAV Secondary Node Air Beam Preparation for High QoS
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current LTE-based solutions fail to meet the high quality of service (QoS) requirements for unmanned aerial vehicles (UAVs) in terms of high upstream data throughput, low latency, and reliability due to limitations in NR cell coverage and lack of UAV-specific features in existing network infrastructure.
Innovation Solution
A method for adding a secondary node (SN) for UAVs, which involves receiving location and flight path information, transmitting air beam preparation requests to candidate SNs, and selecting or determining the SN to prepare an air beam for the UAV, ensuring high QoS requirements are met.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If LTE-based solutions are used for UAV communication, then device compatibility and network infrastructure availability are improved, but upstream data throughput, latency, and reliability deteriorate and cannot meet high QoS requirements
Solution Approach 1:
The patent segments the network into master node (MN) and secondary node (SN) components, where the MN handles control plane functions and the SN provides enhanced user plane resources. This segmentation allows the system to maintain compatibility with existing LTE infrastructure while adding specialized SN resources to improve upstream throughput and meet high QoS requirements for UAV applications.
Solution Approach 2:
The patent implements preliminary action by performing air beam preparation in advance before the UAV actually needs the communication service. The MN receives location information, identifies candidate SNs, and prepares air beams proactively based on predicted UAV positions and flight paths. This preliminary preparation reduces latency and ensures high throughput when the UAV requires communication services.
2Device complexity
If conventional NR cell coverage is used, then network infrastructure simplicity is improved, but coverage reliability and QoS for UAV-specific applications deteriorate
Solution Approach 1:
The patent divides the network infrastructure into MN and SN segments, where the MN maintains existing LTE connectivity and the SN provides enhanced NR resources. This segmentation preserves infrastructure simplicity while improving reliability through coordinated multi-node operation, allowing the system to meet UAV-specific QoS requirements without completely redesigning the network.
Solution Approach 2:
The MN acts as an intermediary between the UAV and the SN, managing the connection and coordinating resources. The MN receives location information from the UAV, selects appropriate SNs, and manages air beam preparation. This intermediary role maintains infrastructure simplicity while enabling reliable high-QoS communication through the additional SN layer.
3Reliability
If air beam preparation is performed for all candidate SNs, then communication reliability is improved, but network resource consumption and processing time worsen
Solution Approach 1:
The patent applies local quality by preparing air beams only for locally relevant candidate SNs based on the UAV's specific location and predicted flight path. Instead of uniform preparation across all SNs, the system identifies and prepares beams only for SNs in the relevant geographic area, reducing overall network resource consumption while maintaining reliability for the specific UAV connection.
Solution Approach 2:
The patent uses partial action by preparing air beams for a selected subset of candidate SNs rather than all possible SNs. The MN evaluates location information and flight path predictions to identify only those SNs that are likely to serve the UAV, preparing beams for this partial set. This approach maintains sufficient reliability while avoiding the excessive resource consumption of universal beam preparation.
4Measurement precision
If location information processing is performed in real-time, then beam preparation accuracy is improved, but processing latency worsens
Solution Approach 1:
The patent implements preliminary action by processing location information and preparing air beams in advance of when the UAV actually needs service. The MN receives location data, predicts future positions based on flight path information, and prepares air beams proactively before the UAV reaches those positions. This approach maintains high beam preparation accuracy while reducing actual service latency.
Solution Approach 2:
The patent applies dynamics by continuously updating location information and re-evaluating candidate SNs as the UAV moves. The system dynamically adjusts beam preparation based on changing UAV positions and flight paths, maintaining accuracy while managing processing latency through adaptive, real-time updates rather than static pre-computation.
Data Source
AI summary
Embodiments of the present disclosure relate to a method and apparatus for adding secondary node (SN) for an unmanned aerial vehicle (UAV). According to an embodiment of the present disclosure, a method can include: receiving location information of an UAV severed by a master node (MN); and transmitting an air beam preparation request for preparing an air beam for the UAV to a first set of candidate SNs with the location information of the UAV, wherein each of the first set of candidate SNs is connected to the MN via a network interface. Embodiments of the present disclosure can meet high QoS requirements in UAV use cases in NR.