Estimation of UFMC Time-Varying Fading Channel Using Adaptive Filters

Abstract

Universal filtered multicarrier (UFMC) modulation technique was suggested as a strong candidate system for future 5G mobile communication systems. Indeed, it combines the advantages of orthogonal frequency division multiplexing (OFDM) and filter bank multicarrier (FBMC) modulation techniques while avoids their drawbacks. UFMC seems to be more effective for future 5G applications and scenarios like a machine to machine (M2M), vehicle to vehicle (V2V), device to device (D2D) and the Internet of Things (IoT). This paper address the estimation and equalization of UFMC time-varying fading channels using adaptive filters based on comb pilot symbols arrangement. To exploit the fading channel statistics, the fading process evolution is modeled by an autoregressive (AR) model and tracked by a Kalman filter. The AR model parameters are obtained by solving the so-called Yule-Walker (YWE) equations based on the Bessel autocorrelation function of the fading channel with known Doppler rate. The result of MATLAB simulation show the effectiveness of the proposed Kalman filter based channel estimator as compared with the conventional ones like recursive least square (RLS) and least mean square (LMS) channel estimator.