Optimal parametric feedforward estimation of frequency-selective fading radio channels

Estimation of time-varying dispersive radio channels is one of the most important tasks of receiver synchronisation. State-of-the-art adaptive estimators employing decision feedback suffer from error propagation and limited robustness against faster fading. In this paper, the optimal feedforward channel estimator using only known training symbols is systematically derived. Statistical channel information is assumed to be available. For moderately rapid fading channels (snapshot assumption), the optimal estimator is shown to be divided into the two subtasks of maximum-likelihood acquisition and subsequent Wiener filtering of the acquired quantities. If perfect training sequences resulting in optimal performance are used, the Wiener filtering operation collapses into independent filtering of the individual acquired tap estimates, and the resulting channel estimator becomes efficient and flexible. The performance of the optimal estimator is evaluated for important cases. A design example of a near-optimal HF channel estimator/receiver is discussed. Linear interpolation is used to reduce the computational complexity of receiver coefficient adjustment. Simulation results confirm the superiority and robustness of feedforward synchronization having near-optimal performance at reduced complexity