Carrier-frequency estimation for space-diversity reception over selective channels

Carrier-frequency estimation for space-diversity reception over frequency-selective channels is discussed. Three estimation schemes based on training sequences are proposed. The first scheme employs arbitrary sequences and provides joint maximum likelihood (ML) estimates of the carrier frequency and the channel response. Its implementation is complex, but its accuracy achieves the Cramer-Rao bound. The second scheme is based on the ML criterion but employs periodic sequences to reduce the computational load. Periodic sequences are also used in the third scheme which is based on heuristic reasoning. Theoretical analysis and simulations are employed to assess the performance of the three estimation methods, and to show the improvements due to space diversity