Impulsive noise rejection for ZigBee communication systems using Error-Balanced Wavelet filtering

Jia, Jia; Meng, Julian

doi:10.1016/j.aeue.2016.01.004

Cited by 8 publications

(2 citation statements)

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“…To calculate the energy consumption for transmitting a k bit data packet at a distance d can be calculated through the energy model given in [2] as:ETxfalse(k,dfalse)=leftEeleck+kEfsd2left1.emif d<d0.leftEeleck+kEmpd4left1.emif d≥d0. where Eelec is the energy consumed per bit to run the transmitter or the receiver circuit, Eampd4 and Efsd2 symbolize the coefficient of transmit amplifier for free space model, while d signify the distance between sender and receiver. Furthermore, the coefficient of transmit amplifier for multi-path model is Eampd4.…”

Section: Preliminariesmentioning

confidence: 99%

“…Underwater Acoustic Networks (UANs) are gaining popularity because of its attractive updated monitoring applications like acoustic chemical waste monitoring, target tracking and detection for military applications, assisted navigation purposes, and monitoring the health of rare marine creatures [1,2,3,4,5]. The oceanic field is very large, deep and in different shapes like square, cylindrical, and rectangular.…”

Section: Introductionmentioning

confidence: 99%

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An Energy-Efficient Redundant Transmission Control Clustering Approach for Underwater Acoustic Networks

Zhao

Fareed

2019

Sensors

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Underwater Acoustic Network (UAN) is an emerging technology with attractive applications. In such type of networks, the control-overhead, redundant inner-network transmissions management, and data-similarity are still very challenging. The cluster-based frameworks manage the control-overhead and redundant inner-network transmissions persuasively. However, the current clustering protocols consume a big part of their energy resources in data-similarity as these protocols periodically sense and forward the same information. In this paper, we introduce a novel two-level Redundant Transmission Control (RTC) approach that ensures the data-similarity using some statistical tests with an appropriate degree of confidence. Later, the Cluster Head (CH) and the Region Head (RH) remove the data-similarity from the original data before forwarding it to the next level. We also introduce a new spatiotemporal and dynamic CH role rotation technique which is capable to adjust the drifted field nodes because of water current movements. The beauty of the proposed model is that the RH controls the communications and redundant transmission between the CH and Mobile Sink (MS), while the CH controls the redundant inner-network transmissions and data-similarity between the cluster members. We conduct simulations to evaluate the performance of our designed framework under different criteria such as average end-to-end delay, the packet delivery ratio, and energy consumption of the network with respect to the recent schemes. The presented results reveal that the proposed model outperforms the current approaches in terms of the selected metrics.

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