Excellent Performance of DFE Based on IT2SNFS in Time-Varying Channels

In this paper, we incorporate an interval type-2 self-organizing neural fuzzy system (IT2SNFS) into decision feedback equalizer (DFE) for time-varying channels. By exploiting the structure and parameter learning algorithms of the IT2SNFS, the proposed DFE is able to obtain the improved performance without the estimation of the channel order. Moreover, the IT2SNFS can set conditions on the increase demand of the fuzzy rules and hence the DFE results in little hardware complexity. We show in simulations that the IT2SNFS-based DFE performs much better than the traditional DFE methods in time-varying channels.