LAUSR

Rayleigh’s distribution is mainly used when fading wireless medium does not have proper line of sight (LOS) path and is dominated by a large number of non-line of sight (NLOS) paths due to reflections of the received signal. Also because of relative motion of the base station and mobile station, a random frequency shift is generally introduced in the carrier, which can be realized in terms of Doppler spread. In case of Rayleigh’s fading channels, there are two critical problems for receiver design that is accurate estimation of channel coefficients followed by mitigation of channel impairments like inter symbol interference and fading in presence of user mobility. The accuracy of estimated channel state information is really crucial to design robust equalizer for reconstruction of bit sequence and the equalizer performance is affected by the fading rate and Doppler spread. The main research contributions of the paper is based on the exploitation of underlying sparseness of block adaptive filters through $$l_{0}$$l0-norm penalty for accurate estimation with stable convergence which helps to design computationally efficient adaptive models for estimation. The accuracy of the proposed sparse block and fast block models is tested using 16 QAM modulation format with Rayleigh’s fading wireless channel for outdoor environments. With the help of MATLAB simulations, the performance of the proposed sparse BLMS and FBLMS adaptive filtering are verified and the detail comparison results are presented.