An Efficient Turbo Equalization for Faster than Nyquist Signal

In this paper, we analyzed efficient decoding scheme with faster than Nyquist (FTN) signaling that is transmission method faster than Nyquist theory and increase the throughput. We proposed BCJR equalization model to minimize inter symbol interference when faster than Nyquist signal is transmitted. The presented model utilized interference as branch information and iteratively exchange probabilistic information between BCJR and LDPC decoder. In BCJR equalizer, the performance depends on Euclidean distance of branch metrics between possible transitions at each node, in order to maximize Euclidean distances, we proposed FTN re-mapper by reordering the branch matrices on trellis diagram. We confirmed that performance was improved compared to conventional methods as increasing throughput of fast than Nyquist signal. 