Mitsubishi electric corporation (20240259062). COMMUNICATION SYSTEM simplified abstract
Contents
COMMUNICATION SYSTEM
Organization Name
mitsubishi electric corporation
Inventor(s)
Tadahiro Shimoda of Tokyo (JP)
Mitsuru Mochizuki of Tokyo (JP)
COMMUNICATION SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240259062 titled 'COMMUNICATION SYSTEM
Simplified Explanation:
The patent application describes a communication system that involves a communication terminal and a base station. The communication terminal encodes data using an encoding model, while the base station decodes the data using a decoding model. The encoding model encodes channel state-related data, and the base station uses machine learning to generate the encoding and decoding models based on learning data, including the channel state-related data.
Key Features and Innovation:
- Communication system with encoding and decoding models for data transmission.
- Encoding model encodes channel state-related data.
- Base station uses machine learning to generate models based on learning data.
- Models are used for encoding and decoding data between communication terminal and base station.
Potential Applications: This technology can be applied in various communication systems, such as wireless networks, IoT devices, and satellite communications.
Problems Solved:
- Efficient encoding and decoding of data in communication systems.
- Adaptation to changing channel states for improved data transmission.
- Utilization of machine learning for model generation in communication systems.
Benefits:
- Enhanced data transmission efficiency.
- Improved communication reliability.
- Adaptability to changing channel conditions.
- Potential for increased data throughput.
Commercial Applications: The technology can be utilized in telecommunications companies, IoT device manufacturers, satellite communication providers, and any industry requiring reliable and efficient data transmission.
Prior Art: Readers can explore prior art related to machine learning in communication systems, encoding and decoding models, and adaptive data transmission techniques.
Frequently Updated Research: Researchers are constantly exploring advancements in machine learning for communication systems, adaptive encoding and decoding techniques, and optimization of data transmission in varying channel conditions.
Questions about Communication Systems: 1. How does machine learning improve data transmission in communication systems? 2. What are the key differences between encoding and decoding models in communication technology?
Original Abstract Submitted
a communication system includes: a communication terminal that encodes transmission data by using an encoding model that encodes and outputs data that has been input; and a base station that decodes data encoded with the encoding model by using a decoding model that, when encoded data is input, decodes and outputs the data, the encoding model performs encoding on channel state-related data that is data on a channel state between the communication terminal and the base station, and the base station executes machine learning using learning data including the channel state-related data in an un-encoded state to generate the encoding model and the decoding model, and notifies the communication terminal of a learning result of the encoding model.