On the Probability of Error and Stochastic Resonance in Discrete Memoryless Channels
Abstract
In this thesis, we studied the performance of Discrete Memoryless Channels (DMC), arising in the context of cooperative underwater wireless sensor networks. We formulated an analytic relationship that relates the average probability of error to the systems parameters, the signal amplitude, the decision threshold and the noise power values. First we studied the trade-off between the signal amplitude and the decision threshold in the special case (2, 2) DMC. Following our (2, 2) DMC model we proposed a symmetric decision threshold to formulate our analytical relationship for the average probability of error based on four arbitrarily defined regions of interest. In order to design a resilient system, conditional probabilities of error are defined with respect to the optimum zero threshold in the (2, 3) DMC. We analyzed 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 focused 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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 2013
- Accession Number
- ADA621290
Entities
People
- Daniel T. Gebremicheal