A Low Complexity Aggregation Method for Underwater On-Pipe Sensor Network

Chenpei Huang, Chaoxian Qi, A. Song, Gangbing Song, Jiefu Chen, Miao Pan
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Abstract

This paper considers the sensor aggregation for underwater pipe-assisted stress wave communication (SWC). Although the SWC is able to support the on-pipe sensor network in short range, the spectrum of long-range SWC is limited due to the effect of reflections at the pipe joints. To address this issue, the orthogonal frequency-division multiplexing (OFDM)-based consensus data aggregation is proposed. Furthermore, the consensus data can be received via time-domain sampling after ’compute-during-transmit’ in multiple access channels (MAC). The simulation results show 0.26%, 0.03%, and 0.08% mean-square-error (MSE) in 5, 10, and 20 sensor aggregation respectively with 5 dB average SNR. A vanishing mean-square-error (MSE) can be observed when increasing either the signal-to-noise ratio (SNR) or the number of sensors. This design can obtain the aggregated data by a simple time domain sampling with no need of down-conversion and demodulation.
水下管道传感器网络的低复杂度聚合方法
研究了水下管道辅助应力波通信(SWC)中的传感器聚集问题。尽管SWC能够在短距离内支持管道上传感器网络,但由于管道接头处反射的影响,远程SWC的频谱有限。为了解决这一问题,提出了基于正交频分复用(OFDM)的一致性数据聚合方法。此外,共识数据可以通过在多址通道(MAC)中“传输期间计算”后的时域采样来接收。仿真结果表明,5、10和20个传感器聚合的均方误差(MSE)分别为0.26%、0.03%和0.08%,平均信噪比为5 dB。当增加信噪比(SNR)或传感器数量时,均方误差(MSE)会消失。该设计无需下变频和解调,只需简单的时域采样即可获得聚合数据。
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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