Estimation of UFMC Fading Channels Using H∞ Filter

Abstract

Universal filtered multi-carrier (UFMC) modulation is a very powerful candidate to be employed for future 5G mobile systems. It overcomes the limitations and restrictions in current modulation techniques employed in 4G mobile systems and supports future applications, such as machineto-machine (M2M), device-to-device (D2D), and vehicle-tovehicle (V2V) communications. In this paper, we address the estimation of UFMC fading channels based on the comb-type pilot arrangement in the frequency domain. The basic solution is to estimate the fading channel based on the mean square error (MSE) or least square (LS) criteria with adaptive implementation using least mean square (LMS) or recursive least square (RLS) algorithms. However, these adaptive filters seem not to be effective, as they cannot fully exploit fading channel statistics, particularly at high Doppler rates. To take advantage of these statistics, time-variations of the fading channel are modeled by an autoregressive process (AR), and are tracked by an H∞ filter. This, however, requires that AR model parameters be known, which are estimated by solving the Yule-Walker equation (YWE), based on the Bessel autocorrelation function (ACF) of the fading channel with a known Doppler rate. Results of Matlab simulations show that the proposed H∞ filter-based channel estimator is more effective when compared with existing estimators

Keywords

• 5G
• autoregressive model
• channel estimation
• fading channe
• H∞ filter
• Kalman filter