Optimum Propagated Signal Selection Using AI for Wireless Communication

Tech ID: 20A001

Competitive Advantages

  • Optimizes wireless communication by efficient signal selection
  • Deep learning techniques ensure strongest relay link
  • This technique shows promising for wireless communications in general such as in vehicle to vehicle communication and wireless sensor networks

Summary

The technology developed by USF researchers applies a deep learning technique called Multi-Layer Perceptron. Since communication signals can be affected by the surrounding environments, the transmitted signal can be reflected, scattered and diffracted via objects that lead to receiving multiple signal components at the receiver side. The MLP method allows for optimum signal selection in an effort to minimize propagation loss and error for wireless communications. It ensures relay selection of the strongest link hence greatly optimizing communications. This can be used by medical diagnostic tools, antennas, and 5G cellular networks. 

 

Propagation Links of a Wireless Communication Where the Destination User Equipment Selects Optimum Link With Lower Loss 

Desired Partnerships

  • License
  • Sponsored Research
  • Co-Development

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