Threshold based Stochastic Resonance for the Binary-Input Ternary-Output Discrete Memoryless Channels

In this paper, we discuss the Stochastic Resonance (SR) effect for the binary-input ternary-output (2,3) Discrete Memoryless Channels (DMC). The (2,3) DMC is of great interest for various digital communications channels, including acoustic underwater communication. We focus on the capacity maximization, brought about by additive Gaussian noise, for the (2,3) DMCs. We analyze the capacity of the threshold binary communication channels in the presence of Additive Gaussian Noise (AGN). In the particular case of binary asymmetric channels with symmetric erasures (BAC/SE) we derive the optimum noise level in order to obtain the maximum capacity. The stochastic resonance for the general binary erasure channel is compared with those of binary symmetric channels. For the general case (2, n) DMC, the Pinsker and Helgert capacity bounds were used for the study of the stochastic resonance. Conference Name: Imaging and Signal Processing in Health Care and Technology