We propose a low complexity graph-based linear minimum mean square error
(LMMSE) equalizer which considers both the intersymbol interference (ISI) and
the effect of non-white noise inherent in Faster-than-Nyquist (FTN) signaling.
In order to incorporate the statistics of noise signal into the factor graph
over which the LMMSE algorithm is implemented, we suggest a method that models
it as an autoregressive (AR) process. Furthermore, we develop a new mechanism
for exchange of information between the proposed equalizer and the channel
decoder through turbo iterations. Based on these improvements, we show that the
proposed low complexity receiver structure performs close to the optimal
decoder operating in ISI-free ideal scenario without FTN signaling through
simulations.Comment: 6 pages, 6 figures, IEEE Wireless Communications and Networking
Conference 2014, Istanbul, Turke
