FPGA implementation of fuzzy sparse adaptive equalizer for indoor wireless communication systems

Abstract

Channel equalization is a basic requirement of wireless receiver to alleviate the effects of inter symbol interference (ISI) that helps in faithful reconstruction of original information. The accuracy of channel state information (CSI) also affects the equalizer performance designed for fading communication channels. The paper proposes a robust decision feedback equalizer (DFE) for indoor wireless channels with limited user mobility using sparse fuzzy modeling. The main contributions of the paper can be realized looking into three important aspects. First, the equalizer is designed for practical indoor channel conditions using adaptive model whose learning parameter is selected using fuzzy rule. Second, the computational complexity is substantially reduced by incorporating norm-based sparsity to the cost function. Third important point is validation of equalization model using Xilinx FPGA and Artix 7 board. QPSK modulated data is transmitted through the channel having non-ideal frequency response which is characterized by IEEE 802.11 model. Further bit error rate(BER), mean square error(MSE), eye diagram and power delay profile(PDP) are taken as the performance measures to test the equalizer in presence of fading effects and user mobility. Both MATLAB simulation and FPGA implementation results are presented to justify the usefulness of the proposed equalization model for indoor wireless communication.