Multi-mode intelligent channel modeling method for machine joint sense enabling

Through the LiDAR point cloud-assisted multimodal intelligent channel modeling method empowered by machine synesthesia, the nonlinear mapping relationship between LiDAR point cloud and electromagnetic propagation diffuser is analyzed and modeled, solving the problem of difficult balance between accuracy and complexity of the existing V2V channel model, and achieving high-precision and scalability channel modeling.

CN119788221AActive Publication Date: 2025-04-08PEKING UNIV
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Patent Information

Application Number
CN202411880046.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-19
Publication Date
2025-04-08
Estimated Expiration
2044-12-19

AI Technical Summary

Technical Problem

The existing V2V channel model is difficult to achieve a good balance between accuracy and complexity, and cannot effectively support the design requirements of 6G V2V systems in ITS, and ignores the mapping relationship between the physical environment and electromagnetic space, resulting in low scalability of the model.

Method used

A multimodal intelligent channel modeling method empowered by machine synesthesia (SoM) is proposed. By analyzing and modeling the nonlinear mapping relationship between LiDAR point cloud and electromagnetic propagation diffuser, a multimodal intelligent channel model is constructed to capture the environment-channel non-stationarity and consistency.

Benefits of technology

It realizes high-precision channel modeling, which is suitable for scenarios under different mobile agent density conditions, improves the scalability and accuracy of the model, and supports algorithm design and performance evaluation of communication systems.

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Abstract

The invention discloses a multi-modal intelligent channel modeling method for machine joint sense enabling, which belongs to the technical field of wireless communication, and comprises the following steps of: designing a scatterer recognition algorithm, intelligently analyzing and modeling a nonlinear mapping relationship between a perception data LiDAR point cloud and an electromagnetic propagation scatterer, and constructing a multi-modal intelligent channel model, so as to realize the modeling of a multi-modal intelligent channel. The method comprises the number, distance, angle, time delay and power parameters of clusters, effectively captures the non-stability and consistency of a wireless communication environment-channel, and can provide a high-precision channel modeling scheme for algorithm design and performance evaluation of a communication system.
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