ANFIS-Based Symbol Recovery in Multi-antenna Stochastic Channels

Since stochastic wireless channels are highly random, fuzzy-based system are suitable options to deal with such uncertainty. This is because of the fact that the fuzzy system provides expert-level decision while tracking microscopic changes. Fuzzy system, however, requires support from artificial neural network (ANN)s for implementing inference rules. When fuzzy and ANN systems are combined, either neuro-fuzzy (NF) or fuzzy-neural (FN) frameworks are derived. Here, we propose an NF-based model for data recovery in multi-antenna setups when transmitted through stochastic wireless channels. Experimental results show that the proposed approach is computationally efficient.