WIRELESS COMMUNICATION METHOD AND APPARATUS

Organization Name

huawei technologies co., ltd.

Inventor(s)

Gongzheng Zhang of Hangzhou (CN)

Rong Li of Boulogne Billancourt (FR)

Yunfei Qiao of Hangzhou (CN)

Jian Wang of Hangzhou (CN)

WIRELESS COMMUNICATION METHOD AND APPARATUS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240323771 titled 'WIRELESS COMMUNICATION METHOD AND APPARATUS

Simplified Explanation: This patent application describes a method and apparatus for wireless communication that involves model ensembling between network devices to improve the performance of a neural network model.

Terminal device obtains a first model of a network device.
Terminal device receives indication information about a second model from another network device.
Terminal device sends information about an ensemble model combining the first and second models back to the second network device.

Key Features and Innovation:

Wireless communication method for knowledge transfer between network devices.
Model ensembling technique to enhance neural network model performance.

Potential Applications: This technology can be applied in various wireless communication systems and networks where model ensembling can optimize neural network performance.

Problems Solved: This technology addresses the need for efficient knowledge transfer and performance improvement in wireless communication systems.

Benefits:

Enhanced performance of neural network models.
Improved efficiency in wireless communication networks.

Commercial Applications: Potential commercial applications include telecommunications, IoT devices, and other wireless communication systems where neural network optimization is crucial for performance.

Prior Art: Readers can explore prior research on model ensembling techniques in wireless communication systems and neural networks.

Frequently Updated Research: Stay updated on the latest advancements in model ensembling and wireless communication technologies to further enhance performance and efficiency.

Questions about Model Ensembling in Wireless Communication: 1. How does model ensembling improve the performance of neural network models in wireless communication systems? 2. What are the key challenges in implementing model ensembling between network devices for knowledge transfer?

Original Abstract Submitted

embodiments of this application provide a wireless communication method and apparatus. the method includes the following: a terminal device obtains a first model of a first network device. the terminal device receives first model indication information from a second network device. the first model indication information indicates a second model of the second network device. the terminal device sends second model indication information to the second network device. the second model indication information indicates an ensemble model of the first model and the second model. according to the methods provided in this application, the terminal device performs model ensembling, to implement knowledge transfer between network devices, thereby improving performance of a neural network model.