Improved Channel Estimation and Removal of Fading for MIMO-OFDM Systems

Abstract

Many inference algorithms develop the time-domain connection of the direct by employ a Kalman filter base on a first-order (or sometimes second-order) estimate of the time-varying channel amid a norm based on link toning (CM), or on the Minimization of Asymptotic Variance (MAV). To decrease the complexity of the high-dimensional RW-KF for combined opinion of the multi-path multifaceted amplitudes, we suggest using an inferior dimensional RW-KF that estimate the compound amplitude of each path separately. We demonstrate that this amounts to a simplification of the joint multi-path Kalman increase formulation through the Woodbury’s identities. Hence, this innovative algorithm consists of a superposition of self-determining single-path single-carrier KFs, which be optimized in our earlier studies. This examination allow us to settle in the optimization to the authentic multi-path multi-carrier scenario, to afford logical formulas for the mean-square error presentation and the best tuning of the future estimator in a straight line as a function of the physical parameter of the canal (Doppler frequency, signal-to-noise-ratio, power delay profile). These logical formula are known for the first-, second-, and third-order RW models used in the KF. The future per-path KF is exposed to be as well-organized as the accurate KF (i.e., the joint multi-path KF), and outperforms the autoregressive-model-based KFs future in the literature.