AN OPTIMUM PULSE AMPLITUDE MODULATION SYSTEM.

Abstract

The optimum (minimum mean square error) linear receiver and transmitter waveform has been jointly determined. The performance of this system is compared with that of the matched filter and the optimum constrained receiver on both a mean square error (MSE) and probability of error (PE) basis. Using the optimum MSE system, performance curves for uncorrelated message sequences are compared with those of correlated sequences. These performance curves are graphs of MSE and PE versus signal to noise (S/N) ratio. Approximating the intersymbol interference distribution with a Gaussian distribution gives PE within a few percent of the exact value. It is found that, for sequences with the same information rate, the correlated sequences have smaller error at low S/N, but at high S/N, the reverse is true. Results are obtained which indicate that, in the absence of accurate information about the message correlation, it is best to design the receiver for an uncorrelated message sequence. The signal energy required to maintain a PE of 0.000001 versus data rate, 1/T, is presented for 2,3, and 4 level data. Finally, it is shown that a channel with colored noise of spectral density N(f) = a + b numerical value of H(f) to the 2nd power where H(f) is the frequency response of the channel, has the same performance as a channel with white noise with spectral density N(f) = a + b and an appropriately chosen channel frequency response function. (Author)

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1966
Accession Number
AD0640735

Entities

People

  • David A. Shnidman

Tags

DTIC Thesaurus Topics

  • Amplitude Modulation
  • Data Rate
  • Frequency
  • Frequency Response
  • Gaussian Distributions
  • Intersymbol Interference
  • Matched Filters
  • Modulation
  • Noise
  • Probability
  • Pulse Amplitude
  • Pulse Amplitude Modulation
  • Sequences
  • Waveforms
  • White Noise

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Radio communications and signal processing.