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Comparing RLS and LMS Adaptive Equalizers for Large Hydrophone Arrays in Underwater Acoustic Communication Channels

机译:在水下声学通信通道中比较RLS和LMS自适应均衡器在水下声学通信通道中的大型水听器阵列

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There is an expected growth in underwater acoustic data traffic. To meet the demand of high data throughput, a migration towards the very high frequency band (>100 kHz) will be necessary. The increment in frequency comes with two problems; high propagation losses and rapid channel fluctuations. One solution addressing both of these obstacles is the use of large hydrophone arrays in combination with multi-channel equalizers. We will in this paper examine and compare tracking properties and convergence rate of the RLS and LMS adaptive algorithm for use in large multichannel equalizers. Using data from a very high frequency (250 kHz) channel we will show that in our channel, for large hydrophone arrays, RLS does not offers a significant advantage over LMS when it comes to tracking channel variations nor convergence rate.
机译:水下声学数据流量存在预期增长。为了满足高数据吞吐量的需求,将需要对非常高频带(> 100 kHz)的迁移。频率增量有两个问题;高传播损耗和快速通道波动。解决这些障碍的一个解决方案是使用大型水听器阵列与多通道均衡器的组合使用。我们将在本文中检查并比较RLS和LMS自适应算法的跟踪属性和收敛速率,用于大型多通道均衡器。使用来自非常高频(250 kHz)通道的数据我们将显示在我们的频道中,对于大型水听器阵列,RLS在跟踪通道变化或收敛速率时,RLS在LMS上没有提供显着优势。

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