18732413. COMMUNICATING A NEURAL NETWORK FORMATION CONFIGURATION simplified abstract (Google LLC)
Contents
COMMUNICATING A NEURAL NETWORK FORMATION CONFIGURATION
Organization Name
Inventor(s)
Jibing Wang of San Jose CA (US)
Erik Richard Stauffer of Mountain View CA (US)
COMMUNICATING A NEURAL NETWORK FORMATION CONFIGURATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18732413 titled 'COMMUNICATING A NEURAL NETWORK FORMATION CONFIGURATION
The patent application describes techniques and apparatuses for enabling base station-user equipment messaging regarding deep neural networks in a wireless communication system.
- A network entity determines a neural network formation configuration for a deep neural network for processing communications in the wireless communication system.
- The network entity communicates the neural network formation configuration to a user equipment.
- The user equipment configures a first neural network based on the neural network formation configuration.
- The user equipment recovers information communicated over the wireless network using the first neural network, allowing the system to adapt to changing conditions and improve information recovery.
Potential Applications: - Enhanced communication systems in wireless networks - Improved data processing and information recovery in real-time applications
Problems Solved: - Adapting to changing operating conditions in wireless communication systems - Enhancing information recovery and data processing efficiency
Benefits: - Increased adaptability and efficiency in wireless communication systems - Improved data processing and information recovery capabilities
Commercial Applications: - Telecom companies for optimizing network performance - IoT devices for real-time data processing and communication
Prior Art: Prior research in neural networks and wireless communication systems may provide insights into similar technologies and applications.
Frequently Updated Research: Stay updated on advancements in deep neural networks and wireless communication technologies for potential improvements in system performance.
Questions about the Technology: 1. How does this technology improve data processing efficiency in wireless communication systems? 2. What are the potential challenges in implementing deep neural networks in user equipment for information recovery in wireless networks?
Original Abstract Submitted
Techniques and apparatuses are described for enabling base station-user equipment messaging regarding deep neural networks. A network entity (base station core network server ) determines a neural network formation configuration (architecture and/or parameter configurations ) for a deep neural network (deep neural network(s) ) for processing communications transmitted over the wireless communication system. The network entity (base station core network server ) communicates the neural network formation configuration to a user equipment (UE ). The user equipment (UE ) configures a first neural network (deep neural network(s) ) based on the neural network formation configuration. In implementations, the user equipment (UE ) recovers information communicated over the wireless network using the first neural network (deep neural network(s) ). This allows the wireless communication system to adapt to changing operating conditions and improve information recovery.
