Partial Ordering and Stochastic Resonance in Discrete Memoryless Channels

Abstract

In this thesis, we study the performance of Discrete Memoryless Channels (DMCs) arising in the context of cooperative underwater wireless sensor networks. We introduce a partial ordering for the binary-input ternary-output (2,3) DMC. In the particular case of the Binary Symmetric Channel with Symmetric Erasure (BSC/SE), we use majorization theory, channel convexity and directional derivative in order to obtain a partial solution to the open problem of partial ordering of the DMCs. In addition, we analyze the stochastic resonance (SR) phenomenon impact upon the performance limits of a distributed underwater wireless sensor networks operating with limited transmitted power and computational capabilities. We focus on the threshold communication systems where, due to the underwater environment, non-coherent communication techniques are affected both by noise and threshold level. The binary-input ternary-output channel is used as a theoretical model for the DMC. We derived the capacity of the threshold (2,3) DMC in the presence of additive noise. In order to evaluate stochastic resonance, we model the theoretical (2,3) DMC as a physical communication channel corrupted by additive noise with different probability distributions. The (2,3) DMC becomes the BSC/SE when the probability density function of the additive noise is an even function such as Gaussian, Laplace, and Cauchy distribution. Due to the complexity and the non-linearity of the channel capacity analytical expression, the Pinsker and Helgert capacity bounds are also used to evaluate the stochastic resonance in the case of the (2,3) DMC. Our contribution consists in improving the state of the art on the issue of partial ordering for the (2,3) DMC and deriving the optimal noise level required to obtain the maximum capacity for a given threshold decision level in the case of the binary-input ternary-output DMC.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
May 01, 2012
Accession Number
AD1016939

Entities

People

  • Roland-yannick K. Kenmogne

Organizations

  • University of the District of Columbia

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Channel Capacity
  • Communication Channels
  • Communication Systems
  • Computer Science
  • Detectors
  • Distribution Functions
  • Electrical Engineering
  • Gaussian Noise
  • Information Theory
  • Military Research
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Random Variables
  • Sensor Networks
  • Signal Processing
  • Wireless Sensor Networks

Readers

  • Linear Algebra
  • Radio communications and signal processing.