A Code Division Multiple Access Communication System for the Low Frequency Band.

Abstract

In this thesis, a code division multiple access (CDMA) communication system for the low frequency (LF) channel is proposed, discussed and analyzed. This LF/CDMA scheme is similar to classical CDMA schemes in that K users share a channel by phase modulating their transmissions with signature sequences. Our LF/CDMA scheme is different in that each user's signature sequence set consists of M orthogonal sequences and thus log (2)M bits of information are transmitted by choosing among the signature sequences. Additionally, the users use r-phase modulation and our model includes an impulsive (non-Gaussian) noise source to model LF atmospheric noise. We derive a locally optimum (small signal) receiver structure for our LF/CDMA scheme. This receiver consists of a bandpass correlator followed by a sampler, a zero memory nonlinearity and M discrete time matched filter/correlators. We analyze the performance of this structure in combined multiple access, impulsive and Gaussian noise. When the noise is dominated by either its multiple access or Gaussian component, the receiver predominantly operates in the linear region of the nonlinearity and performance is similar to that of a linear receiver.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1983
Accession Number
ADA142378

Entities

People

  • P. K. Enge

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acquisition
  • Code Division Multiple Access
  • Communication Systems
  • Detectors
  • Electrical Engineering
  • Engineering
  • Frequency
  • Frequency Bands
  • Gaussian Noise
  • Information Science
  • Information Theory
  • Matched Filters
  • Multiple Access
  • Phase Modulation
  • Probability
  • Random Variables
  • Sequence Analysis

Fields of Study

  • Engineering

Readers

  • Control Systems Engineering.
  • Radar Systems Engineering.
  • Statistical inference.