Main Article Content
Ultra-wideband (UWB) communication systems cover enormous bandwidths that have strongly low-power spectral densities. At UWB communication system with high data rate, owing to multipath propagation, the spread delay in inter symbol interference (ISI) will raise the bit error rate (BER) considerably. ISI which is formed via the UWB channels can be removed by equalization, which is one of the most significant signal processing techniques. Furthermore, LMS algorithm represents a very efficient tool for determining adaptive equalizer coefficients values in communication systems, in spite of that, the LMS adaptive equalizer encounters response diminishing besides slow convergence rate. The current paper adopts an adaptive equalizer based adaptive neuron-fuzzy inference system (ANFIS). The simulation outcomes reveal that the convergence rates as well as accuracy of identification of ANFIS based algorithm are surpass the traditional LMS algorithm, moreover, simulation outcomes prove that ISI is effectively limited and the performance of the system is clearly improved.
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