Cyclic-feature based Doppler scale estimation for orthogonal frequency-division multiplexing (OFDM) signals over doubly selective underwater acoustic channels

Abstract

Underwater acoustic (UWA) communications enable underwater wireless networks to be applied in various applications, such as oceanographic research, pollution early-warning, disaster prevention, and military systems. However, a major challenge in UWA communications is to combat the Doppler distortion caused by doubly selective (time and frequency selective) channels. Most Doppler scale estimators rely on training data or specially designed packet structures. These methods have fundamental limitations in transmission rate and spectral efficiency. Different from these methods, this paper presents a Doppler scale estimation approach exploiting the redundant information contained within the cyclic prefix (CP) or cyclic suffix (CS) of orthogonal frequency-division multiplexing (OFDM) signals. We analyze the cyclic features of OFDM signals over doubly selective underwater channels in order to demonstrate the relationship between the cyclic features and the Doppler scale. Based on the theoretical analyses, we find that the Doppler scale can be estimated from the extremums of the cyclic autocorrelation function (CAF) of the received signal. Simulations validate our theoretical analyzes and the performance of the proposed Doppler scale estimator. Apart from the high estimation performance, we also highlight the utility of our method when only few OFDM blocks are available.