Information Theoretical Studies of Non-Gaussian Noise Channels and Markovian Constrained Relay Channels
Linyun Huang
10.26180/5cec916962002
https://bridges.monash.edu/articles/thesis/Information_Theoretical_Studies_of_Non-Gaussian_Noise_Channels_and_Markovian_Constrained_Relay_Channels/8188748
Communications in non-Gaussian noise channel and communication network with memory are two important but difficult frontiers of information theory. In this thesis, I studied these two areas. In the first part of this thesis, the Gaussian mixture distribution is adopted to model the non-Gaussian noise behaviour, typically found in powerline communications, man-made electromagnetic interferences, and underwater communications. Here, the capacity of a Gaussian mixture noise channel and its capacity-achieving input distribution
are investigated. In the second part, I studied the capacity of a Markovian
constrained relay channel and the maxentropic state transition probabilities
for relay transmitter are derived. The derived results have been verified via a
number of simulations.
2019-05-28 01:39:51
Information Theory
Communication Theory
Relay channel
Channel capacity
non-Gaussian noise
Markovian constraint
Markov chain
Coding and Information Theory