A state-space approach to multiuser parameters estimation using central difference for CDMA systems

In this paper, it is shown that a state-space model applies to the code-division multiple-access (CDMA) channel, and Central Difference Filter (CDF) produces channel estimates with the minimum mean-square error (MMSE). This result may be used as compare to Extended Kalman Filter (EKF) which used as channel estimator in CDMA system. The main purpose of this paper is to compare robustness of channel estimator for realistic rapidly time-varying Rayleigh fading channels. To overcome the highly nonlinear nature of time delay estimation and also improve the accuracy, consistency and efficiency of channel estimation, an iterative nonlinear filtering algorithm, called the CDF has been applied in the field of CDMA System. The proposed channel estimator has a more near-far resistant property than the conventional Extended Kalman Filter (EKF). Thus, it is believed that the proposed estimator can replace well-known filters, such as the EKF. The Cramer-Rao lower bound (CRLB) is derived for the estimator, and simulation result show that it is nearly near-far resistant and clearly outperforms the EKF.