Efficient Adaptive Turbo Equalization for Multiple-Input–Multiple-Output Underwater Acoustic Communications

Abstract

An efficient adaptive turbo equalization (ATEQ) scheme is proposed for multiple-input–multiple-output underwater acoustic (UWA) communications. The proposed ATEQ scheme utilizes two layers of iterative processing: The inner-layer iteration is the soft-decision-based equalizer parameters adaptation and filtering of received signals in the equalizer, and the outer-layer iteration is the Turbo exchange of extrinsic log-likelihood ratio between the equalizer and decoder. In contrast, the existing ATEQ schemes use hard-decision symbols for filter adaptation but soft symbols for filtering and Turbo iteration. When the adaptive filters are designed and updated via the normalized least mean squares (NLMS) or the improved proportionate NLMS algorithms for low computational complexity and good channel tracking, the soft symbols utilized in both the pilot-assisted and the decision-directed modes of the proposed ATEQ scheme achieve fast convergence with short training sequences, thus achieving high spectrum efficiency. The proposed scheme is evaluated by the field trail data collected in the 2008 Surface Processes and Acoustic Communications Experiment. The results demonstrate that the proposed ATEQ scheme is robust against the severe triply-selective UWA channels and mitigate slow-convergence problem commonly suffered by direct-adaptation equalizers.