18543390. NEURAL NETWORK BASED CHANNEL STATE INFORMATION FEEDBACK simplified abstract (QUALCOMM Incorporated)

NEURAL NETWORK BASED CHANNEL STATE INFORMATION FEEDBACK

Organization Name

QUALCOMM Incorporated

Inventor(s)

Taesang Yoo of San Diego CA (US)

Weiliang Zeng of San Diego CA (US)

Naga Bhushan of San Diego CA (US)

Krishna Kiran Mukkavilli of San Diego CA (US)

Tingfang Ji of San Diego CA (US)

Yongbin Wei of La Jolla CA (US)

Sanaz Barghi of Carlsbad CA (US)

NEURAL NETWORK BASED CHANNEL STATE INFORMATION FEEDBACK - A simplified explanation of the abstract

This abstract first appeared for US patent application 18543390 titled 'NEURAL NETWORK BASED CHANNEL STATE INFORMATION FEEDBACK

Simplified Explanation

Various aspects of the present disclosure generally relate to neural network based channel state information (CSI) feedback. In some aspects, a device may obtain a CSI instance for a channel, determine a neural network model including a CSI encoder and a CSI decoder, and train the neural network model based at least in part on encoding the CSI instance into encoded CSI, decoding the encoded CSI into decoded CSI, and computing and minimizing a loss function by comparing the CSI instance and the decoded CSI. The device may obtain one or more encoder weights and one or more decoder weights based at least in part on training the neural network model. Numerous other aspects are provided.

• Device obtains CSI instance for a channel
• Device determines neural network model with CSI encoder and decoder
• Neural network model is trained by encoding and decoding CSI instance, minimizing loss function
• Encoder and decoder weights are obtained based on training

Potential Applications

This technology could be applied in wireless communication systems to improve the efficiency and accuracy of channel state information feedback.

Problems Solved

This technology solves the problem of efficiently encoding and decoding channel state information in wireless communication systems using neural networks.

Benefits

The benefits of this technology include improved performance, reduced complexity, and enhanced reliability in wireless communication systems.

Potential Commercial Applications

• Wireless communication systems
• Telecommunication networks
• Internet of Things (IoT) devices

Possible Prior Art

One possible prior art in this field is the use of traditional signal processing techniques for channel state information feedback in wireless communication systems.

Unanswered Questions

How does this technology compare to existing methods of channel state information feedback in terms of performance and efficiency?

The article does not provide a direct comparison between this technology and existing methods in terms of performance and efficiency.

What are the potential limitations or challenges of implementing this technology in real-world wireless communication systems?

The article does not address the potential limitations or challenges of implementing this technology in real-world wireless communication systems.

Original Abstract Submitted

Various aspects of the present disclosure generally relate to neural network based channel state information (CSI) feedback. In some aspects, a device may obtain a CSI instance for a channel, determine a neural network model including a CSI encoder and a CSI decoder, and train the neural network model based at least in part on encoding the CSI instance into encoded CSI, decoding the encoded CSI into decoded CSI, and computing and minimizing a loss function by comparing the CSI instance and the decoded CSI. The device may obtain one or more encoder weights and one or more decoder weights based at least in part on training the neural network model. Numerous other aspects are provided.