Qualcomm incorporated (20240113919). RECURRENT EQUIVARIANT INFERENCE MACHINES FOR CHANNEL ESTIMATION simplified abstract

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 20240113919 titled 'RECURRENT EQUIVARIANT INFERENCE MACHINES FOR CHANNEL ESTIMATION

Simplified Explanation

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

• 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 associated with multiple layers.

Potential Applications

This technology can be applied in:

• 5G and beyond wireless communication systems
• Internet of Things (IoT) devices
• Autonomous vehicles

Problems Solved

• Improved channel estimation accuracy
• Efficient resource allocation in wireless networks
• Enhanced data transmission reliability

Benefits

• Higher data rates and throughput
• Reduced interference and latency
• Enhanced overall network performance

Potential Commercial Applications

Optimized resource allocation for:

• Telecommunication companies
• Smart city infrastructure
• Industrial automation systems

Possible Prior Art

One possible prior art could be the use of traditional channel estimation techniques in wireless communications, which may not be as accurate or efficient as the methods described in this patent application.

How does this technology impact battery life in wireless devices?

This article does not address the potential impact of the described technology on the battery life of wireless devices. It would be important to understand if the increased accuracy and efficiency of channel estimation have any implications for power consumption.

Are there any limitations to the scalability of this technology in large-scale wireless networks?

The article does not discuss any potential limitations to the scalability of the technology in large-scale wireless networks. It would be valuable to explore how this method performs when applied to networks with a high number of connected devices.

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.