Gradient Estimation Vector Modeling of signal attenuation in Underwater Wireless Sensor Networks

J. Iqbal, F. Ahmed, M. Ishaque, Muhammad Hassan Nasir
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引用次数: 2

Abstract

A paradigm of novel-networking is presented by the Underwater Wireless Sensor Networks (UWSNs) when compared to Terrestrial Wireless Sensor Networks. Its not straightforward, instead, basic challenges need to be addressed for the deployment of UWSNs due to the environment type found underwater. UWSNs have to depend on other physical means such as acoustic signals for the transmission as the electromagnetic waves cannot be transmitted over a long distance in underwater environment. Large latency and low bandwidth are the key features of underwater wireless link as compared to the wireless link among ground-based sensors. The nature of transmission medium and physical properties of the environment of underwater acoustic channels are temporally and spatially variable. High variations occurring in underwater acoustic channels result in high uncertainties to precisely model the signal attenuation which is dependent on transmission link length and frequency. This paper has been intended to address such type of uncertainties and closely examine even minor variations occurring in signal attenuation in cases of spherical and cylindrical spreading. These variations have been addressed by using a mathematical modeling technique as `Gradient Estimation Vector'. It is the technique for systematically changing parameters in a model to determine the effects of such changes. Gradient Estimation Vectors actually characterize the signal attenuation more precisely along with the variations and uncertainties involved.
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水下无线传感器网络中信号衰减的梯度估计矢量建模
将水下无线传感器网络(UWSNs)与陆地无线传感器网络进行了比较,提出了一种新型组网模式。这并不简单,相反,由于水下环境类型,部署uwsn需要解决基本挑战。由于电磁波在水下环境中无法进行长距离传输,因此水下无线传感器网络的传输必须依靠声信号等其他物理手段。与地面传感器间的无线链路相比,水下无线链路的主要特点是时延大、带宽低。水声信道传输介质的性质和环境的物理性质在时间和空间上都是可变的。水声信道的高度变化导致信号衰减随传输链路长度和频率的精确建模存在很大的不确定性。本文旨在解决这种类型的不确定性,并仔细检查在球形和圆柱形扩散的情况下信号衰减发生的微小变化。这些变化已经通过使用“梯度估计向量”的数学建模技术来解决。它是一种系统地改变模型中的参数以确定这种变化的影响的技术。梯度估计向量实际上更准确地描述了信号衰减以及所涉及的变化和不确定性。
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