Qualcomm incorporated (20240340660). PERFORMANCE MONITORING FOR ARTIFICIAL INTELLIGENCE (AI)/MACHINE LEARNING (ML) FUNCTIONALITIES AND MODELS simplified abstract
PERFORMANCE MONITORING FOR ARTIFICIAL INTELLIGENCE (AI)/MACHINE LEARNING (ML) FUNCTIONALITIES AND MODELS
Organization Name
Inventor(s)
Eren Balevi of Brooklyn NY (US)
Taesang Yoo of San Diego CA (US)
Rajeev Kumar of San Diego CA (US)
PERFORMANCE MONITORING FOR ARTIFICIAL INTELLIGENCE (AI)/MACHINE LEARNING (ML) FUNCTIONALITIES AND MODELS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240340660 titled 'PERFORMANCE MONITORING FOR ARTIFICIAL INTELLIGENCE (AI)/MACHINE LEARNING (ML) FUNCTIONALITIES AND MODELS
Simplified Explanation: The patent application describes systems and techniques for wireless communications, where a wireless device can transmit capability information related to machine learning models to a network entity and receive performance targets in return.
Key Features and Innovation:
- Wireless device transmitting capability information related to machine learning models to a network entity.
- Receiving performance targets associated with specific functionalities from the network entity.
Potential Applications: This technology can be applied in various wireless communication systems to enhance performance and efficiency.
Problems Solved: This technology addresses the need for efficient communication between wireless devices and network entities by utilizing machine learning models.
Benefits:
- Improved communication performance.
- Enhanced efficiency in wireless networks.
Commercial Applications: Potential commercial applications include telecommunications, IoT devices, and other wireless communication systems where performance optimization is crucial.
Prior Art: Readers can explore prior art related to wireless communication systems, machine learning in telecommunications, and performance optimization in wireless networks.
Frequently Updated Research: Stay updated on research related to machine learning applications in wireless communications and performance optimization in network systems.
Questions about Wireless Communications: 1. What are the key benefits of utilizing machine learning models in wireless communications? 2. How does the transmission of capability information improve communication performance in wireless networks?
Original Abstract Submitted
systems and techniques are disclosed for performing wireless communications. for example, a wireless device (e.g., a user equipment (ue)) can transmit (or output for transmission), to a network entity, capability information related to a first functionality supported by a set of machine learning (ml) models of the apparatus. the wireless device can receive, from the network entity, a performance target associated with the first functionality.
