A method and system for modeling real-time short-range near-ground radio transmission loss
By constructing an electromagnetic environment sensing system and a lightweight neural network model, the real-time and accuracy issues of transmission loss assessment in short-range wireless communication are solved, enabling efficient and low-latency assessment of edge devices, which is applicable to scenarios such as intelligent connected vehicles and industrial IoT.
Patent Information
- Authority / Receiving Office
- CN Β· China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHENGDU UNIV
- Filing Date
- 2026-06-10
- Publication Date
- 2026-07-10
AI Technical Summary
Existing technologies cannot assess transmission loss in short-range wireless communication in real time with high accuracy. In particular, the assessment accuracy is insufficient under dynamic weather changes and obstacle obstruction. Moreover, existing models have a large number of parameters and high inference overhead, making it difficult to achieve lightweight and universal assessment on resource-constrained edge devices.
An electromagnetic environment sensing system is constructed. By collecting and fusing datasets under controlled and variable conditions, a lightweight neural network model is used to learn the nonlinear mapping between environmental parameters and transmission loss, thereby achieving millisecond-level real-time assessment.
It achieves high-precision, low-overhead assessment of near-ground radio transmission loss within 1000 meters, is suitable for adaptive link optimization of edge devices, and improves the reliability and real-time performance of communication systems.
Smart Images

Figure CN122372124A_ABST