Investigation and Simulation of Nonlinear Processors for Spread Spectrum Receivers. Volume 2. Users Manual

Abstract

The objective of the recent research effort was to investigate and determine the viability of utilizing Locally Optimal (LO) nonlinear processing to mitigate non-Gaussian interfering signals in a Direct Sequence (DS) SS communications system. The effort centered on the use of memoryless techniques, as well as techniques employing memory, and performance comparisons of many receiver and nonlinear processor configurations. The approach used included the analysis and evaluation of several implementation of the various nonlinear processing algorithms. The analysis included the study of well known techniques, as well as newly developed methods. Evaluation was accomplished through the development of software simulations designed to test the algorithms in various signaling scenarios. The results illustrate the tradeoffs of each nonlinear processor algorithm for use in a spread spectrum receiver. This knowledge can be used to determine the most effective processor for a given interference scenario. The work presented in this report is directly in line with the mission of Rome Laboratory (RL) to provide secure, reliable communications to the United States Air Force. Adaptive Filtering, Nonlinear Processing, Spread Spectrum

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1993
Accession Number
ADA278026

Entities

People

  • Donald R. Ucci
  • Jimm Grimm
  • William Jacklin

Organizations

  • Illinois Institute of Technology

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Cartesian Coordinates
  • Communication Systems
  • Continuous Waves
  • Distribution Functions
  • Engineering
  • Fourier Series
  • Frequency
  • Gaussian Noise
  • Illinois
  • Modulation
  • Sequences
  • Simulations
  • Spread Spectrum
  • Two Dimensional
  • United States

Fields of Study

  • Engineering

Readers

  • Control Systems Engineering.
  • Radio communications and signal processing.
  • Software Engineering