18054896. GENERATIVE WIRELESS CHANNEL MODELING simplified abstract (QUALCOMM Incorporated)

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GENERATIVE WIRELESS CHANNEL MODELING

Organization Name

QUALCOMM Incorporated

Inventor(s)

Tribhuvanesh Orekondy of Biel (CH)

Arash Behboodi of Amsterdam (NL)

Joseph Binamira Soriaga of San Diego CA (US)

Max Welling of Bussum (NL)

GENERATIVE WIRELESS CHANNEL MODELING - A simplified explanation of the abstract

This abstract first appeared for US patent application 18054896 titled 'GENERATIVE WIRELESS CHANNEL MODELING

Simplified Explanation

The patent application describes techniques for wireless channel modeling using a generative adversarial network (GAN). Here is a simplified explanation of the abstract:

  • A set of input data is received, which represents data transmitted from a transmitter as a signal 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 expected behavior of the wireless channel.

Potential applications of this technology:

  • Wireless network planning and optimization: The generated channel model can be used to simulate and analyze the behavior of wireless channels, helping in the planning and optimization of wireless networks.
  • Performance evaluation: The simulated output data can be used to evaluate the performance of different wireless communication systems and protocols.
  • Antenna design: The channel model can assist in designing and optimizing antenna systems by providing insights into the behavior of wireless channels.

Problems solved by this technology:

  • Accurate wireless channel modeling: The use of a generative adversarial network allows for the creation of realistic channel models that accurately represent the behavior of wireless channels.
  • Cost-effective testing: Instead of relying solely on expensive and time-consuming field testing, the generated channel model can be used to simulate various scenarios and evaluate system performance in a cost-effective manner.

Benefits of this technology:

  • Improved network planning: By accurately modeling wireless channels, network planners can make informed decisions to optimize coverage, capacity, and quality of service.
  • Faster development and testing: The use of simulated output data reduces the need for extensive field testing, enabling faster development and testing of wireless communication systems.
  • Cost savings: By reducing the reliance on field testing, this technology can lead to significant cost savings in the design, deployment, and maintenance of wireless networks.


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.

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