Wi-Fi Auto-Encoder Parameter Exchange for Accurate Frame Decoding
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Solution Overview
Problem
There is no specific implementation for applying AI/ML to WLAN, which fails to enhance network performance and user experience.
Innovation Solution
An AI model parameter interaction method and apparatus using auto-encoders and classifiers in Wi-Fi transmitters and receivers to transmit and decode data frames with special sequences, enabling parameter updates and enhancements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If AI/ML algorithms are applied to WLAN, then network performance and user experience are enhanced, but there is no specific implementation method available
Solution Approach 1:
The patent implements self-service by enabling Wi-Fi devices to automatically perform AI model parameter embedding, special sequence transmission, and model updates without manual configuration. The system autonomously monitors feedback messages, detects parameter update needs, and executes training workflows, making AI/ML application in WLAN accessible without requiring implementation guidance
2Measurement precision
If data frames are transmitted using auto-encoder with special sequences, then encoding efficiency and decoding accuracy are improved, but device complexity increases
Solution Approach 1:
The patent applies universality by designing the auto-encoder to perform multiple functions: it embeds AI model parameters, transmits data frames with special sequences, and enables model updates. The same transmission mechanism serves both data communication and AI model synchronization purposes, reducing the need for separate dedicated systems
Solution Approach 2:
The patent implements nesting by embedding AI model parameters within existing Wi-Fi data frames and using special sequences nested within the frame structure. The classifier extracts and processes these nested elements, allowing AI functionality to be integrated within the existing Wi-Fi protocol framework rather than requiring a completely separate system
Data Source
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AI summary
Provided are an Al model parameter interaction method and apparatus. The method is performed by a Wi-Fi transmitter, and comprises: after Al model parameters are embedded into an auto-encoder of the Wi-Fi transmitter, transmitting a data frame with a special sequence to a Wi-Fi receiver by means of the auto-encoder of the Wi-Fi transmitter, so that the Wi-Fi receiver identifies the data frame according to the special sequence, and decodes the data frame by means of an auto-encoder of the Wi-Fi receiver when successfully identifying the data frame. The auto-encoder improves the encoding efficiency and decoding accuracy of conventional Wi-Fi transmitters and receiver systems, thereby enhancing Wi-Fi network performance and user experience, and solves the problem in the related art that there is no specific implementation of applying AI/ML to WLAN, which fails to achieve the effect of enhancing network performance and user experience by means of AI/ML.