Hybrid ANN reducing training time requirements and decision delay for equalization in presence of co-channel interference

Bayesian equalizer is known to be the optimum equalizer. This paper proposes a Hybrid Artificial Neural Network (Hybrid ANN) and an algorithm to modify Decision Feedback Equalizer (DFE) function of Bayesian equalizer while equalizing in presence of co-channel interference (CCI). A combination of Artificial Neural Network and Decision Feedback Equalizer (DFE) is termed as Neural-DFE (NDFE). The results show that the decision delay and training time requirement reduces significantly by use of NDFE. This creates an advantage specifically for a mobile environment where the CCI is varying in nature and the Bayesian equalizer requires a lot of training time.