17756841. Machine Learning-Based Beam Selection simplified abstract (Apple Inc.)

Machine Learning-Based Beam Selection

Organization Name

Apple Inc.

Inventor(s)

Yushu Zhang of Beijing (CN)

Dawei Zhang of Saratoga CA (US)

Haitong Sun of Cupertino CA (US)

Huaning Niu of San Jose CA (US)

Oghenekome Oteri of San Diego CA (US)

Seyed Ali Akbar Fakoorian of San Diego CA (US)

Sigen Ye of San Diego CA (US)

Wei Zeng of Saratoga CA (US)

Weidong Yang of San Diego CA (US)

Machine Learning-Based Beam Selection - A simplified explanation of the abstract

This abstract first appeared for US patent application 17756841 titled 'Machine Learning-Based Beam Selection

Simplified Explanation

A user equipment (UE) is designed to choose a beam in a wireless network. The UE receives a beam pattern configuration from a base station, selects a subset of beams for measurements, performs measurements, updates a beam search space (BSS) based on the measurements, reports the updated BSS to the base station, and switches to a beam from the updated BSS.

Key Features and Innovation

• User equipment (UE) selecting a beam in a wireless network.
• Receiving beam pattern configuration from a base station.
• Performing measurements on a subset of beams.
• Updating a beam search space (BSS) based on measurements.
• Reporting the updated BSS to the base station.
• Switching to a beam from the updated BSS.

Potential Applications

This technology can be applied in various wireless communication systems where beamforming is used to improve signal quality and coverage.

Problems Solved

This technology addresses the challenge of efficiently selecting and switching between beams in a wireless network to optimize performance.

Benefits

• Improved signal quality.
• Enhanced network coverage.
• Efficient beam selection and switching.
• Enhanced overall network performance.

Commercial Applications

• Telecommunications industry for 5G networks.
• IoT devices requiring reliable wireless connections.
• Satellite communication systems for improved data transmission.

Prior Art

Readers can explore prior research on beamforming techniques in wireless communication systems to understand the evolution of this technology.

Frequently Updated Research

Stay updated on the latest advancements in beamforming technology in wireless networks to leverage the most recent innovations for improved network performance.

Questions about Beam Selection in Wireless Networks

How does beamforming technology impact network efficiency?

Beamforming technology enhances network efficiency by focusing signal transmission in specific directions, reducing interference, and improving overall network performance.

What are the key considerations when selecting beams in a wireless network?

Key considerations when selecting beams include signal strength, interference levels, and network coverage requirements.

Original Abstract Submitted

A user equipment (UE) is configured to select a beam. The UE receives, from a base station of a wireless network, a beam pattern configuration, reports, to the base station, a subset of beams on which measurements will be performed, performs measurements on the subset of beams, updates a beam search space (BSS) based on the measurements, reports the updated BSS to the base station and selects a beam from the updated BSS to switch to.