Google llc (20240202528). WIRELESS SYSTEM EMPLOYING END-TO-END NEURAL NETWORK CONFIGURATION FOR DATA STREAMING simplified abstract

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WIRELESS SYSTEM EMPLOYING END-TO-END NEURAL NETWORK CONFIGURATION FOR DATA STREAMING

Organization Name

google llc

Inventor(s)

Jibing Wang of San Jose CA (US)

Erik Richard Stauffer of Sunnyvale CA (US)

WIRELESS SYSTEM EMPLOYING END-TO-END NEURAL NETWORK CONFIGURATION FOR DATA STREAMING - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240202528 titled 'WIRELESS SYSTEM EMPLOYING END-TO-END NEURAL NETWORK CONFIGURATION FOR DATA STREAMING

Simplified Explanation:

The patent application describes systems and techniques for training and implementing a chain of neural networks along a wireless transmission path to efficiently transmit data between devices without the need for individual coding and decoding processes.

  • Neural networks are trained and implemented along a wireless transmission path.
  • Source-side networks handle data encoding and channel encoding.
  • Sink-side networks handle channel decoding and data decoding.
  • End-to-end transmission is achieved without discrete coding and decoding stages.
  • The process can adapt to various operational parameters.

Key Features and Innovation:

  • Training and implementation of neural networks along a wireless transmission path.
  • Integration of encoding and decoding processes within the neural network chain.
  • Adaptability to different operational parameters for efficient data transmission.

Potential Applications:

  • Wireless communication systems
  • Data transmission in IoT devices
  • Telecommunication networks

Problems Solved:

  • Eliminates the need for separate coding and decoding processes.
  • Enhances efficiency in data transmission.
  • Facilitates adaptation to changing operational parameters.

Benefits:

  • Streamlined data transmission process
  • Improved efficiency in wireless communication
  • Adaptability to different network conditions

Commercial Applications:

  • Wireless communication technology for IoT devices
  • Telecommunication networks optimization
  • Data transmission systems for various industries

Prior Art:

Prior research in neural network-based data encoding and decoding processes in wireless communication systems.

Frequently Updated Research:

Ongoing research on neural network optimization for wireless data transmission.

Questions about Neural Network Chain for Wireless Data Transmission:

1. How does the integration of encoding and decoding processes within the neural network chain improve data transmission efficiency? 2. What are the potential challenges in adapting the end-to-end neural network chaining process to different operational parameters?


Original Abstract Submitted

systems and techniques provide for the joint training and implementation of an end-to-end chain of neural networks along the nodes of an at least partially wireless transmission path used to transmit a data stream between a data source device and at least one data sink device. the source-side neural networks of the chain can implement one or both of data encoding and channel encoding of outgoing data blocks, and the sink-side neural networks of the chain conversely can implement one or both of channel decoding and data decoding to provide efficient end-to-end transmission of the data stream without necessitating individual design, test, and implementation of discrete processes for each coding and decoding stage, while also facilitating the adaptation of the end-to-end neural network chaining process to various operational parameters.

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