Quasi-Optimal Processing in Spread Spectrum Environments.

Abstract

The derivations of robust Locally Optimum (LO) detection algorithms (high interference/signal ratios) with and without memory, and their performance in a spread spectrum communications system, are the subject of this report. There are three forms of LO detection considered: (1) detection with memory; (2) detection in independent and identically distributed (iid) noise; and (3) memoryless detection. Several algorithms are investigated, all using the usual assumption that the small signal corrupting the noise estimate is acceptable. Simulation results show, however, that this assumption is not always valid, even in high interferencel signal ratio environments. Detailed investigations focused on regions of poor performance, using ideal signal-free estimates of the noise as a baseline. The ideal estimator yielded a truly robust detector over a wide range of scenarios. Recommended research should thus be focused on means for obtaining true noise estimates in practical environments.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1996
Accession Number
ADA321811

Entities

People

  • Donald R. Ucci
  • John Tanas
  • William R. Jacklin

Organizations

  • Illinois Institute of Technology

Tags

Communities of Interest

  • Advanced Electronics
  • C4I
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Command And Control
  • Communication Systems
  • Computational Science
  • Detection
  • Detectors
  • Environment
  • Estimators
  • Fourier Series
  • Frequency
  • Information Theory
  • Probability
  • Random Variables
  • Signal Processing
  • Simulations
  • Spread Spectrum
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Radio communications and signal processing.
  • Statistical inference.