Underwater Acoustic Channels (UAC) have inherent sparse characteristics. The traditional adaptive equalization techniques do not utilize this feature to improve the performance. In this paper we consider the Variable Adaptive Subgradient Projection (V-ASPM) method to derive a new sparse equalization algorithm based on the Minimum Symbol Error Rate (MSER) criterion. Compared with the original MSER algorithm, our proposed scheme adds sparse matrix to the iterative formula, which can assign independent step-sizes to the equalizer taps. How to obtain such proper sparse matrix is also analyzed. On this basis, the selection scheme of the sparse matrix is obtained by combining the variable step-sizes and equalizer sparsity measure. We call the new algorithm Sparse-Control Proportional-MSER (SC-PMSER) equalizer. Finally, the proposed SC-PMSER equalizer is embedded into a turbo receiver, which perform turbo decoding, Digital Phase-Locked Loop (DPLL), time-reversal receiving and multi-reception diversity. Simulation and real-field experimental results show that the proposed algorithm has better performance in convergence speed and Bit Error Rate (BER).

水下声学通道 (UAC) 具有固有的稀疏特性。传统的自适应均衡技术没有利用这个特性来提高性能。在本文中，我们考虑了可变自适应次梯度投影 (V-ASPM) 方法，以基于最小符号错误率 (MSER) 准则推导出一种新的稀疏均衡算法。与原始 MSER 算法相比，我们提出的方案在迭代公式中增加了稀疏矩阵，可以为均衡器抽头分配独立的步长。还分析了如何获得这种合适的稀疏矩阵。在此基础上，结合可变步长和均衡器稀疏度量，得到稀疏矩阵的选择方案。我们将新算法称为 Sparse-Control Proportional-MSER (SC-PMSER) 均衡器。最后，建议的 SC-PMSER 均衡器嵌入到 Turbo 接收器中，该接收器执行 Turbo 解码、数字锁相环 (DPLL)、时间反转接收和多接收分集。仿真和现场实验结果表明，该算法在收敛速度和误码率（BER）方面具有较好的性能。