Apple inc. (20240188167). SYSTEMS, METHODS, AND DEVICES FOR UE-ASSISTED PRIVACY-AWARE DATA-DRIVEN NW CONTROL simplified abstract
Contents
- 1 SYSTEMS, METHODS, AND DEVICES FOR UE-ASSISTED PRIVACY-AWARE DATA-DRIVEN NW CONTROL
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SYSTEMS, METHODS, AND DEVICES FOR UE-ASSISTED PRIVACY-AWARE DATA-DRIVEN NW CONTROL - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
SYSTEMS, METHODS, AND DEVICES FOR UE-ASSISTED PRIVACY-AWARE DATA-DRIVEN NW CONTROL
Organization Name
Inventor(s)
Said Medjkouh of San Diego CA (US)
Tarik Tabet of Carlsbad CA (US)
Kenza Hamidouche of Cupertino CA (US)
Ayman F. Naguib of Cupertino CA (US)
Sreevalsan Vallath of Dublin CA (US)
SYSTEMS, METHODS, AND DEVICES FOR UE-ASSISTED PRIVACY-AWARE DATA-DRIVEN NW CONTROL - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240188167 titled 'SYSTEMS, METHODS, AND DEVICES FOR UE-ASSISTED PRIVACY-AWARE DATA-DRIVEN NW CONTROL
Simplified Explanation
The patent application focuses on user equipment (UE) assisted privacy-aware data-driven network control in wireless communication networks. The system involves UEs, base stations, an aggregation and analysis system, and a data-driven network control unit working together to enhance network efficiency through machine learning tools and information exchange while maintaining user privacy.
- UEs, base stations, aggregation and analysis system, and data-driven network control unit collaborate to improve wireless communication network efficiency.
- Machine learning tools are utilized for training, developing, and using models to optimize network control.
- Information of varying privacy levels is exchanged, protected, and anonymized to enable privacy-aware data-driven network control.
Potential Applications
This technology can be applied in various industries such as telecommunications, IoT, and smart cities to enhance network performance while ensuring user privacy.
Problems Solved
1. Enhances network efficiency through data-driven control. 2. Maintains user privacy while exchanging information for network optimization.
Benefits
1. Improved network performance. 2. Enhanced user privacy protection. 3. Efficient data-driven network control.
Potential Commercial Applications
"Privacy-Aware Data-Driven Network Control in Wireless Communication Networks" can be utilized by telecommunications companies, IoT providers, and smart city developers to optimize network operations and protect user privacy.
Possible Prior Art
There may be prior art related to machine learning tools in network optimization and privacy-aware data exchange in wireless communication networks.
Unanswered Questions
How does this technology impact network security?
This article does not delve into the specific security measures implemented to protect the exchanged information and ensure network security.
What are the potential limitations of this technology in real-world implementations?
The article does not address any potential challenges or limitations that may arise when implementing this technology in practical scenarios.
Original Abstract Submitted
solutions for user equipment (ue) assisted privacy-aware data-driven network (nw) control. ues, base stations, an aggregation and analysis system, and a data-driven nw control unit may coordinate and communicate with one another to enhance the efficiency and effectiveness of a wireless communication network by implementing machine learning tools and exchanging information in a manner that enables the training, development, and use of models. information of various levels of privacy may be exchanged, protected, anonymized, etc., to enable ue-assisted privacy-aware data-driven nw control while still protecting the privacy of individual users.
