18472083. RECURRENT EQUIVARIANT INFERENCE MACHINES FOR CHANNEL ESTIMATION simplified abstract (QUALCOMM Incorporated)

RECURRENT EQUIVARIANT INFERENCE MACHINES FOR CHANNEL ESTIMATION

Organization Name

QUALCOMM Incorporated

Inventor(s)

Kumar Pratik of Amsterdam (NL)

Arash Behboodi of Amsterdam (NL)

Pouriya Sadeghi of San Diego CA (US)

Tharun Adithya Srikrishnan of Mountain View CA (US)

Alexandre Pierrot of San Diego CA (US)

Joseph Binamira Soriaga of San Diego CA (US)

Gautham Hariharan of Sunnyvale CA (US)

Supratik Bhattacharjee of San Diego CA (US)

RECURRENT EQUIVARIANT INFERENCE MACHINES FOR CHANNEL ESTIMATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 18472083 titled 'RECURRENT EQUIVARIANT INFERENCE MACHINES FOR CHANNEL ESTIMATION

Simplified Explanation

The abstract describes methods, systems, and devices for wireless communications, specifically focusing on channel estimation using a combination of minimum mean square estimation (MMSE) and nonlinear two-dimensional interpolation techniques.

• Wireless device receives a set of resources associated with a channel, including subsets for data transmission and reference signals.
• Device generates multiple channel estimations per layer of the channel using MMSE operation and nonlinear interpolation.
• Refinement operation is performed to generate a channel estimation for multiple layers.

Potential Applications

This technology can be applied in various wireless communication systems, such as 5G networks, IoT devices, and satellite communications, to improve channel estimation accuracy and overall system performance.

Problems Solved

1. Enhanced channel estimation accuracy: By utilizing MMSE and nonlinear interpolation techniques, this innovation addresses the challenge of accurately estimating channel conditions in wireless communication systems. 2. Efficient resource allocation: The method of allocating resources for data transmission and reference signals helps optimize the use of available bandwidth and improve overall system efficiency.

Benefits

1. Improved signal quality: By generating accurate channel estimations, this technology can enhance signal quality and reliability in wireless communications. 2. Enhanced system performance: The combination of MMSE and nonlinear interpolation techniques can lead to better overall system performance, including higher data rates and lower latency.

Potential Commercial Applications

"Wireless Channel Estimation Technology in 5G Networks" This technology can be utilized in 5G network infrastructure, IoT devices, and satellite communication systems to enhance channel estimation accuracy and improve overall wireless communication performance.

Possible Prior Art

One possible prior art in this field is the use of linear interpolation techniques for channel estimation in wireless communication systems. However, the combination of MMSE and nonlinear interpolation as described in this patent application represents a novel approach to address the challenges of accurate channel estimation in modern wireless networks.

Unanswered Questions

How does this technology impact battery life in wireless devices?

The abstract does not provide information on the potential impact of this technology on the battery life of wireless devices. It would be interesting to know if the channel estimation techniques described have any implications for power consumption.

Can this technology be implemented in real-time communication systems?

It is not clear from the abstract whether the channel estimation methods can be applied in real-time communication systems. Understanding the feasibility of real-time implementation would be crucial for assessing the practicality of this innovation.

Original Abstract Submitted

Methods, systems, and devices for wireless communications are described. A wireless device may receive an assignment of a set of resources associated with a channel, where the set of resources includes a first subset of resources allocated for data transmission and a second subset of resources allocated for a reference signal. The wireless device may generate, from the reference signal in accordance with a minimum mean square estimation (MMSE) operation, a first set of multiple channel estimations per layer of the channel. The wireless device may generate, in accordance with a nonlinear two-dimensional interpolation of the channel, a second set of multiple channel estimations per layer of the channel and may perform a refinement operation utilizing the estimations to generate a channel estimation associated with multiple layers.