18481806. USER EQUIPMENT AND BASE STATION OPERATING BASED ON COMMUNICATION MODEL, AND OPERATING METHOD THEREOF simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)
Contents
- 1 USER EQUIPMENT AND BASE STATION OPERATING BASED ON COMMUNICATION MODEL, AND OPERATING METHOD THEREOF
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 USER EQUIPMENT AND BASE STATION OPERATING BASED ON COMMUNICATION MODEL, AND OPERATING METHOD THEREOF - 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
USER EQUIPMENT AND BASE STATION OPERATING BASED ON COMMUNICATION MODEL, AND OPERATING METHOD THEREOF
Organization Name
Inventor(s)
Youngseok Jung of Suwon-si (KR)
USER EQUIPMENT AND BASE STATION OPERATING BASED ON COMMUNICATION MODEL, AND OPERATING METHOD THEREOF - A simplified explanation of the abstract
This abstract first appeared for US patent application 18481806 titled 'USER EQUIPMENT AND BASE STATION OPERATING BASED ON COMMUNICATION MODEL, AND OPERATING METHOD THEREOF
Simplified Explanation
The devices, systems, and techniques described herein provide for efficient integration of machine learning techniques into wireless communication system frameworks. User equipment may perform communication with base stations based on communication models generated through machine learning. Data may be collected from various communication environments to optimize communication models (e.g., to train communication models, provide inputs to communication models, etc.). According to embodiments of the present disclosure, user equipment may update parameters (e.g., parameters for controlling wireless communication systems) to provide the user equipment with various data (e.g., data subsequent to modifying parameters of the wireless communication system) for enabling effective training and implementation of communication models that are implemented based on machine learning. Accordingly, user equipment may efficiently manage communication models based on various data, and user equipment may thus perform communication operations within wireless communication systems with improved performance (e.g., based on the generated and updated optimal communication models).
- Efficient integration of machine learning techniques into wireless communication system frameworks
- User equipment communication with base stations based on machine learning-generated models
- Data collection from various communication environments to optimize communication models
- User equipment updating parameters for effective training and implementation of communication models
- Improved performance in wireless communication systems based on optimal communication models
Potential Applications
The technology described in this patent application could be applied in various industries such as telecommunications, IoT, smart cities, and autonomous vehicles for enhancing wireless communication systems' performance and efficiency.
Problems Solved
This technology solves the problem of effectively integrating machine learning techniques into wireless communication systems, optimizing communication models, and improving overall system performance based on generated and updated models.
Benefits
The benefits of this technology include enhanced communication efficiency, improved system performance, optimized communication models, and better user experience in wireless communication environments.
Potential Commercial Applications
One potential commercial application of this technology could be in the development of advanced wireless communication systems for industries such as telecommunications, IoT, smart cities, and autonomous vehicles.
Possible Prior Art
One possible prior art in this field could be research papers or patents related to machine learning integration in wireless communication systems, optimization of communication models, and parameter updates for improved system performance.
Unanswered Questions
== How does this technology handle real-time communication scenarios in wireless systems? The patent abstract does not specifically mention how the technology deals with real-time communication scenarios in wireless systems. It would be interesting to know if the system can adapt quickly to changing communication environments and requirements.
== What are the potential limitations or challenges of implementing machine learning in wireless communication systems? The abstract does not address any potential limitations or challenges that may arise when implementing machine learning in wireless communication systems. It would be valuable to understand any constraints or obstacles that could affect the practical application of this technology.
Original Abstract Submitted
The devices, systems, and techniques described herein provide for efficient integration of machine learning techniques into wireless communication system frameworks. User equipment may perform communication with base stations based on communication models generated through machine learning. Data may be collected from various communication environments to optimize communication models (e.g., to train communication models, provide inputs to communication models, etc.). According to embodiments of the present disclosure, user equipment may update parameters (e.g., parameters for controlling wireless communication systems) to provide the user equipment with various data (e.g., data subsequent to modifying parameters of the wireless communication system) for enabling effective training and implementation of communication models that are implemented based on machine learning. Accordingly, user equipment may efficiently manage communication models based on various data, and user equipment may thus perform communication operations within wireless communication systems with improved performance (e.g., based on the generated and updated optimal communication models).
