20230155704. GENERATIVE WIRELESS CHANNEL MODELING simplified abstract (QUALCOMM Incorporated)
Contents
GENERATIVE WIRELESS CHANNEL MODELING
Organization Name
Inventor(s)
Tribhuvanesh Orekondy of Biel (CH)
Arash Behboodi of Amsterdam (NL)
Joseph Binamira Soriaga of San Diego CA (US)
GENERATIVE WIRELESS CHANNEL MODELING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20230155704 titled 'GENERATIVE WIRELESS CHANNEL MODELING
Simplified Explanation
The abstract of the patent application describes techniques for wireless channel modeling using a generative adversarial network (GAN). Here is a simplified explanation:
- A set of input data is received, which represents data transmitted from a transmitter in a wireless channel.
- A channel model is created for the wireless channel using a generative adversarial network (GAN), which is a type of machine learning model.
- The channel model is trained to generate a set of simulated output data by transforming the input data.
- The simulated output data represents the behavior of the wireless channel.
Potential applications of this technology:
- Wireless network planning and optimization: The channel model can be used to simulate different wireless channel conditions and optimize network configurations.
- Performance evaluation: The simulated output data can be used to evaluate the performance of wireless communication systems and algorithms.
- Antenna design: The channel model can aid in the design and testing of antennas for wireless communication.
Problems solved by this technology:
- Accurate wireless channel modeling: The use of a generative adversarial network allows for more realistic and accurate modeling of wireless channels.
- Cost-effective testing: Simulating the wireless channel behavior reduces the need for expensive and time-consuming field testing.
Benefits of this technology:
- Improved network performance: By accurately modeling the wireless channel, network configurations can be optimized for better performance.
- Cost and time savings: Simulating the wireless channel behavior reduces the need for extensive field testing, saving both time and resources.
- Enhanced design capabilities: The channel model can assist in the design and testing of wireless communication systems, leading to improved antenna designs and overall system performance.
Original Abstract Submitted
certain aspects of the present disclosure provide techniques for wireless channel modeling. a set of input data is received for data transmitted, from a transmitter, as a signal in a wireless channel. a channel model is generated for the wireless channel using a generative adversarial network (gan). a set of simulated output data is generated by transforming the first set of input data using the channel model.
