Enabaling LPI/LPD in Wireless Communications Through Deep Learning

Abstract

The goal of this activity is to develop machine learning techniques to enable resource and latency efficient communication systems. Traditionally, communication system design has focused on exploiting traditional tools such as adaptive signal processing and coding theoretic approaches to determine the best detection, estimation and encoding/decoding algorithms for communication systems. The benefit of doing so is that we obtain explicit algorithms that present provable performance guarantees, such as convergence, error rates and throughput.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2019
Accession Number
AD1092036

Entities

People

  • Sriram Vishwanath

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Amplitude Modulation
  • Coding
  • Communication Systems
  • Computer Programming
  • Computer Programs
  • Data Science
  • Decoding
  • Deep Learning
  • Gaussian Noise
  • Machine Learning
  • Modulation
  • Multiple Input Multiple Output
  • Neural Networks
  • Signal Processing
  • Simulations
  • Standards

Fields of Study

  • Computer science

Readers

  • Mathematical Modeling and Probability Theory.
  • Radio communications and signal processing.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks