Enabaling LPI/LPD in Wireless Communications Through Deep Learning

Abstract

The goal of this proposed activity is to bring machine learning closer to solving challenges in the physical layer of communication systems. Traditionally, communication system design has focused on exploiting tools such as adaptive signal processing and coding theoretic approaches to determine the best detection, estimation and encoding/decoding algorithms for communication systems. The advantage of the power of machine learning to improve performance is to reduce latency and improve accuracy of communication theoretic physical layer algorithms. In this proposal, we aim to better understand the benefits of machine learning in aiding communication systems. Specifically, our focus will be on detection and decoding in communication systems.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 14, 2019
Source ID
W911NF1810422

Entities

People

  • Sriram Vishwanath

Organizations

  • Army Contracting Command
  • United States Army
  • University of Texas at Austin

Tags

Fields of Study

  • Computer science
  • Engineering

Readers

  • Distributed Systems and Data Platform Development
  • Neural Network Machine Learning.
  • Radio communications and signal processing.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks