GUANGDONG OPPO MOBILE TELECOMMUNICATIONS CORP., LTD. (20240323059). DATA ACQUISITION METHOD AND APPARATUS, AND DEVICE, MEDIUM, CHIP, PRODUCT AND PROGRAM simplified abstract
Contents
- 1 DATA ACQUISITION METHOD AND APPARATUS, AND DEVICE, MEDIUM, CHIP, PRODUCT AND PROGRAM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DATA ACQUISITION METHOD AND APPARATUS, AND DEVICE, MEDIUM, CHIP, PRODUCT AND PROGRAM - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Data Acquisition Technology
- 1.13 Original Abstract Submitted
DATA ACQUISITION METHOD AND APPARATUS, AND DEVICE, MEDIUM, CHIP, PRODUCT AND PROGRAM
Organization Name
GUANGDONG OPPO MOBILE TELECOMMUNICATIONS CORP., LTD.
Inventor(s)
DATA ACQUISITION METHOD AND APPARATUS, AND DEVICE, MEDIUM, CHIP, PRODUCT AND PROGRAM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240323059 titled 'DATA ACQUISITION METHOD AND APPARATUS, AND DEVICE, MEDIUM, CHIP, PRODUCT AND PROGRAM
Simplified Explanation
The patent application describes a method for acquiring data using a generative model, an electronic device, and a chip. The method involves acquiring reference signal sample data and channel information sample data generated by a generative model trained on a generative adversarial network (GAN) using real reference signals and real channel information.
- Acquiring data using a generative model
- Training the generative model on a GAN
- Using real reference signals and channel information for training
- Acquiring reference signal sample data and channel information sample data
- Training a channel estimation model
Key Features and Innovation
- Utilizes a generative model trained on a GAN for data acquisition
- Incorporates real reference signals and channel information into the training process
- Enables the training of a channel estimation model using the acquired data
Potential Applications
The technology can be applied in various fields such as telecommunications, wireless communication, signal processing, and machine learning.
Problems Solved
The technology addresses the need for efficient data acquisition methods in channel estimation and signal processing applications.
Benefits
- Improved accuracy in channel estimation
- Enhanced performance in wireless communication systems
- Efficient data acquisition process
Commercial Applications
Title: Advanced Data Acquisition Technology for Wireless Communication Systems This technology can be commercialized in industries such as telecommunications, IoT devices, and network infrastructure providers. It can improve the performance and reliability of wireless communication systems, leading to better user experience and increased efficiency in data transmission.
Prior Art
Readers can explore prior research on generative models, GANs, and channel estimation methods in the fields of telecommunications and signal processing to understand the background of this technology.
Frequently Updated Research
Researchers are continually exploring advancements in generative models, GANs, and channel estimation techniques to enhance data acquisition processes in wireless communication systems.
Questions about Data Acquisition Technology
How does the use of a generative model improve data acquisition in wireless communication systems?
The use of a generative model allows for the generation of realistic reference signal sample data and channel information sample data, which can enhance the training of channel estimation models for improved accuracy.
What are the potential challenges in implementing this technology in real-world applications?
Some potential challenges in implementing this technology may include optimizing the training process of the generative model, ensuring compatibility with existing communication systems, and addressing any privacy or security concerns related to data acquisition.
Original Abstract Submitted
a method for acquiring data, an electronic device and a chip are provided. the method for acquiring data includes that: reference signal sample data and channel information sample data that are generated by a generative model are acquired. herein, the generative model is obtained through training based on a generative adversarial network (gan), real reference signals and real channel information, and the reference signal sample data and the channel information sample data are used for training a channel estimation model.
