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作 者:刘璐[1,2,3] 郑睿 LIU Lu;ZHENG Rui(National Key Laboratory of Underwater Acoustic Technology,Harbin Engineering University,Harbin 150001;Key Laboratory of Marine Information Acquisition and Security(Harbin Engineering University),Ministry of Industry and Information Technology,Harbin 150001;College of Underwater Acoustic Engineering,Harbin Engineering University,Harbin 150001)
机构地区:[1]哈尔滨工程大学水声技术全国重点实验室,哈尔滨150001 [2]工业和信息化部海洋信息获取与安全工信部重点实验室(哈尔滨工程大学),哈尔滨150001 [3]哈尔滨工程大学水声工程学院,哈尔滨150001
出 处:《声学学报》2024年第5期1041-1050,共10页Acta Acustica
摘 要:针对具有稀疏性的水声信道,提出了一种参数自适应调整稀疏迭代最小二乘自适应算法。通过联合优化遗忘因子和稀疏约束参数,实现不同结构特性稀疏信道的自适应匹配,使均衡算法更快地收敛到稳态;针对常规均衡算法和单一方向Turbo判决反馈均衡器存在误差传递的问题,设计了一种稀疏自适应迭代最小二乘算法与双向迭代Turbo判决反馈均衡器相结合的均衡器结构,改善了常规均衡算法和单一方向Turbo判决反馈均衡器误差传递的问题,提高了在稀疏水声信道条件中自适应均衡器的收敛速度和均衡性能。仿真和试验数据结果表明,在稀疏水声信道中,基于参数自适应调整稀疏迭代最小二乘算法的双向Turbo均衡算法具有更快的收敛性能、更低的误比特率和更好的均衡效果。This paper proposes a parameter-adaptive adjustment sparse recursive least-square(PAA-S-RLS)adaptive algorithm for the sparse underwater acoustic channel.Firstly,the proposed algorithm can achieve adaptive matching of sparse channels with different structures by jointly optimizing the forgetting factor and sparse penalty parameters,which enables the equalization algorithm converge to the steady-state faster.Secondly,a robust sparse adaptive RLS algorithm combined with bidirectional iterative Turbo decision feedback equalizer is designed to address the issue of error propagation caused by the conventional equalization algorithms and conventional Turbo decision feedback equalizer,which can improve the convergence rate and the performance of adaptive equalizers in sparse underwater acoustic channels.Simulation and experimental results show that the bidirectional iterative equalization algorithm based on adaptive adjustment sparse RLS has faster convergence rate,lower bit error rate,and better equalization performance in the sparse underwater acoustic channel.
分 类 号:TN929.3[电子电信—通信与信息系统]
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