基于LoRa网络的自适应心跳帧识别与远程数据传输方法
By collecting multi-dimensional link parameters in real time in the LoRa network and performing adaptive heartbeat message generation and reverse closed-loop optimization, the channel congestion and energy consumption problems of LoRa network in complex environments are solved, and a dynamic balance between link reliability and terminal energy consumption is achieved, thereby improving network throughput and system stability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SICHUAN YUANWEIMIN TECH CO LTD
- Filing Date
- 2026-04-27
- Publication Date
- 2026-07-17
AI Technical Summary
The existing heartbeat frame mechanism of LoRa networks suffers from high channel congestion risk, delayed link health perception, and low terminal energy utilization efficiency in complex dynamic electromagnetic environments, making it difficult to achieve dynamic scheduling and resource optimization of communication links in large-scale, high-reliability application scenarios.
By collecting multi-dimensional link parameters in real time at the terminal side, dynamically generating adaptive heartbeat messages, and implementing reverse closed-loop optimization of frame recognition and transmission parameters at the gateway side, combined with cross-layer scheduling of the network server, the link health quantification and adaptive adjustment of heartbeat frequency are realized, thereby optimizing remote data transmission.
It achieves the goal of minimizing terminal power consumption and increasing network throughput while ensuring the reliability of communication links. It solves the problem of reliability and power consumption imbalance in complex environments of traditional static heartbeat mechanisms, and provides technical support for the long-term stable operation of large-scale Internet of Things systems.
Smart Images
Figure CN122420183A_ABST