Minimum Symbol-Error Rate Based Adaptive Decision Feedback Equalizer in Underwater Acoustic Channels

Adaptive linear equalizer, whose coefficients are designed to be adjustable to the channel impulse response, has emerged as a simple and efficient technique to adaptively compensate for the channel fading. However, conventional adaptive linear equalizers suffer from performance degradation and slow convergence in the underwater acoustic channel with large delay spread. To solve this problem, in this paper, we propose a novel adaptive decision-feedback equalizer (DFE) based on the minimum symbol-error rate (MSER) criterion. Specifically, by taking the sample-by-sample adaptation into account, the problem is first formulated as minimizing the norm between two consecutive adaptations under the constraint that the latest adaptation will provide correct detection for both the current and past symbols. Then we solve the optimization problem by using the Lagrange multiplier method to obtain the adaptive DFE that minimizes the sequential symbol detection error with a fast convergence rate. Simulation results show that the proposed MSER-based adaptive DFE significantly outperforms the existing equalizers in terms of convergence speed and steady-state performance for underwater acoustic channels.