Efficient Decision Feedback Equalizers for Wireless Communication Using Optimum Filter Weights Selection and Normalized Channel Model

Decision feedback equalizers are widely used non-linear equalizers which are used to reduce the inter symbol interference in the communication systems. Selection of proper weights for forward and feedback filters is very important for the designing of efficient decision feedback equalizers. Performance of the most of existing wireless communication systems degrades under higher PSK (Phase Shift Keying) sizes. But use of higher PSK size is essential to fulfill the demand of high speed broadband wireless communication. In this paper an efficient block based decision feedback equalizer is proposed in a training mode. It is proposed to model the multipath Rayleigh fading channel with normalized channel impulse response (CIR) and measured AWGN (Additive White Gaussian Noise). This significantly improves the performance of wireless communication systems with M-PSK modulation techniques for higher PSK size of 512 and 1024. In addition BER (Bit Error rate) performance of the wireless communication system is evaluated by varying forward and feedback filter weights for RLS (Recursive Least Square ) based decision feedback equalizers. Based on the performance evaluation an optimum fuzzy weight selection rule is proposed for providing minimized smooth BER curves.