Artificial Intelligence Based Under Water Acoustic Channel Equalizer Design

Fatma Ceren Yücel, Meryem Maras, Talat Kepezkaya, Elif Nur Ayvaz, A. Özen
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Abstract

In this study, it is suggested to use artificial intelligence assisted fuzzy logic based LMS (F-LMS) algorithm to improve the performance of single carrier (SC) underwater acoustic communication (UWAC) systems in multipath underwater acoustic channel environments. Numerical simulation studies are carried out to compare the proposed F-LMS algorithm with the bit error rate (BER) and mean square error (MSE) performance measures over decision feedback equalizer (DFE) and channel matched filter DFE (CMF-DFE). From the produced numerical results, it is understood that the best gains are achieved in both MSE and BER simulations with the proposed F-LMS algorithm. In addition to these, the most important contribution of the proposed study is to eliminate the error floor that occurs in DFE equalizers in BER simulations with CMF-DFE equalizers.
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基于人工智能的水声通道均衡器设计
本研究提出利用人工智能辅助的基于模糊逻辑的LMS (F-LMS)算法提高单载波水声通信(UWAC)系统在多径水声信道环境下的性能。通过数值仿真研究,比较了所提出的F-LMS算法与决策反馈均衡器(DFE)和信道匹配滤波器(CMF-DFE)的误码率(BER)和均方误差(MSE)性能。从所产生的数值结果中可以理解,使用所提出的F-LMS算法在MSE和BER模拟中都获得了最佳增益。除此之外,本研究最重要的贡献是消除了使用CMF-DFE均衡器进行误码率模拟时DFE均衡器中出现的误差层。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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