Abstract:
It is proposed that a dynamic Bayesian network (DBN) is used to perform turbo equalization in a system transmitting
information over a Rayleigh fading multipath channel. The DBN turbo equalizer (DBN-TE) is modeled on a single
directed acyclic graph by relaxing the Markov assumption and allowing weak connections to past and future states. Its
complexity is exponential in encoder constraint length and approximately linear in the channel memory length.
Results show that the performance of the DBN-TE closely matches that of a traditional turbo equalizer that uses a
maximum a posteriori equalizer and decoder pair. The DBN-TE achieves full convergence and near-optimal
performance after small number of iterations.
