Meta platforms technologies, llc (20240211660). SYSTEMS AND METHODS FOR ANTENNA DESIGN simplified abstract

SYSTEMS AND METHODS FOR ANTENNA DESIGN

Organization Name

meta platforms technologies, llc

Inventor(s)

Weiping Dou of Cupertino CA (US)

Yuandong Tian of San Carlos CA (US)

Andrew Cohen of San Francisco CA (US)

Jiang Zhu of Cupertino CA (US)

Geng Ye of Union City CA (US)

Ulf Jan Ove Mattsson of Campbell CA (US)

Peter Eli Renner of San Jose CA (US)

Beidi Chen of Pittsburgh PA (US)

Xiaomeng Yang of Sunnyvale CA (US)

Kevin Stone of San Luis Obispo CA (US)

Slawomir Marcin Koziel of Kopavogur (IS)

SYSTEMS AND METHODS FOR ANTENNA DESIGN - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240211660 titled 'SYSTEMS AND METHODS FOR ANTENNA DESIGN

The disclosed computer-implemented method involves using a machine-learning model to generate a set of antenna designs, tokenizing each design, predicting the frequency response for each tokenized design, comparing the responses, and selecting the best design based on performance criteria.

• Utilizes a machine-learning model to generate antenna designs
• Tokenizes each antenna design for analysis
• Predicts the frequency response for each tokenized design
• Compares the frequency responses to determine the best design
• Selects an antenna design that meets performance thresholds

Potential Applications: - Antenna design optimization - Wireless communication systems - IoT devices - Radar systems - Satellite communication

Problems Solved: - Efficient antenna design selection process - Improved performance of wireless communication systems - Enhanced signal reception and transmission

Benefits: - Faster and more accurate antenna design optimization - Increased efficiency in wireless communication systems - Enhanced signal quality and reliability

Commercial Applications: Title: "Machine-Learning-Based Antenna Design Optimization for Wireless Communication Systems" This technology can be utilized by telecommunications companies, IoT device manufacturers, radar system developers, and satellite communication providers to enhance the performance of their products and services.

Questions about Machine-Learning-Based Antenna Design Optimization: 1. How does machine learning improve the efficiency of antenna design optimization? Machine learning enables the generation, analysis, and selection of antenna designs based on performance criteria, leading to faster and more accurate results.

2. What are the potential implications of this technology on the telecommunications industry? This technology could revolutionize the way antenna designs are optimized, leading to improved wireless communication systems and enhanced signal quality for various applications.

Original Abstract Submitted

the disclosed computer-implemented method may include generating, using a machine-learning model of a computing device, a set of antenna designs. the method may also include tokenizing, by the computing device, each antenna design in the generated set of antenna designs. additionally, the method may include predicting, by the machine-learning model of the computing device, a frequency response for each tokenized antenna design. furthermore, the method may include comparing, by the computing device, the frequency response for each tokenized antenna design. finally, the method may include selecting, by the computing device based on the comparison, an antenna design that meets a performance threshold for the frequency response. various other methods, systems, and computer-readable media are also disclosed.