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Uncoded acoustic communication in shallow waters with bursty impulsive noise

机译:在浅水区的未编制的声学通信,具有突发的冲动噪音

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The shallow underwater acoustic channel offers a challenging environment. Besides long delay spreads caused by multiple surface-bottom reflections, the channel is time variant as well. In tropical waters, the problem is compounded further by impulsive noise created by snapping shrimp. Conventionally, the noise process is modeled by white impulsive noise. However, in reality, snapping shrimp noise depicts memory and is thus bursty as well. We investigate the performance of a high-rate uncoded acoustic communication system operating in tropical shallow waters. The stationary α-sub-Gaussian noise with memory order m (αSGN(m)) model is employed as it characterizes both the temporal and amplitude statistics of snapping shrimp noise. We show that there is a stark deviation from the expected performance of the white maximum-likelihood (ML) detector when the ambient noise is αSGN(m) (m > 0). Moreover, we derive the ML detector for the shallow water acoustic channel with additive αSGN(m) and compare its performance to that of its white counterpart.
机译:浅水区频道提供挑战性的环境。除了由多个表面底部反射引起的长延迟差,频道也是时间变体。在热带水域中,通过捕获虾产生的冲动噪音进一步复合问题。传统上,噪声过程由白色脉冲噪声建模。然而,实际上,捕捉虾噪声描绘了记忆,因此也是突发的。我们研究了在热带浅水中运行的高速型未编码声学通信系统的性能。具有存储器顺序M的静止α-亚高斯噪声(αSgn(m))模型,因为它表征了捕获虾噪声的时间和幅度统计。我们表明,当环境噪声是αsgn(m)(m> 0)时,存在与白色最大似然(m1)检测器的预期性能的差异。此外,我们推导出浅水声通道的ML检测器,具有添加剂αsgn(m),并将其性能与其白色对应物的性能进行比较。

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