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无线供电传感器网络中的簇合作:建模与性能分析

Cluster Cooperation in Wireless-Powered Sensor Networks: Modeling and Performance Analysis.

作者信息

Zhang Chao, Zhang Pengcheng, Zhang Weizhan

机构信息

School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

出版信息

Sensors (Basel). 2017 Sep 27;17(10):2215. doi: 10.3390/s17102215.

DOI:10.3390/s17102215
PMID:28953231
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5676671/
Abstract

A wireless-powered sensor network (WPSN) consisting of one hybrid access point (HAP), a near cluster and the corresponding far cluster is investigated in this paper. These sensors are wireless-powered and they transmit information by consuming the harvested energy from signal ejected by the HAP. Sensors are able to harvest energy as well as store the harvested energy. We propose that if sensors in near cluster do not have their own information to transmit, acting as relays, they can help the sensors in a far cluster to forward information to the HAP in an amplify-and-forward (AF) manner. We use a finite Markov chain to model the dynamic variation process of the relay battery, and give a general analyzing model for WPSN with cluster cooperation. Though the model, we deduce the closed-form expression for the outage probability as the metric of this network. Finally, simulation results validate the start point of designing this paper and correctness of theoretical analysis and show how parameters have an effect on system performance. Moreover, it is also known that the outage probability of sensors in far cluster can be drastically reduced without sacrificing the performance of sensors in near cluster if the transmit power of HAP is fairly high. Furthermore, in the aspect of outage performance of far cluster, the proposed scheme significantly outperforms the direct transmission scheme without cooperation.

摘要

本文研究了一种由一个混合接入点(HAP)、一个近簇和相应远簇组成的无线供电传感器网络(WPSN)。这些传感器由无线供电,通过消耗从HAP发射的信号中收集的能量来传输信息。传感器能够收集能量并存储收集到的能量。我们提出,如果近簇中的传感器没有自己的信息要传输,作为中继,它们可以以放大转发(AF)的方式帮助远簇中的传感器将信息转发到HAP。我们使用有限马尔可夫链对中继电池的动态变化过程进行建模,并给出了具有簇协作的WPSN的通用分析模型。通过该模型,我们推导出了作为该网络指标的中断概率的闭式表达式。最后,仿真结果验证了本文设计的出发点以及理论分析的正确性,并展示了参数如何影响系统性能。此外,还可知,如果HAP的发射功率相当高,远簇中传感器的中断概率可以在不牺牲近簇中传感器性能的情况下大幅降低。此外,在远簇的中断性能方面,所提出的方案明显优于无协作的直接传输方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/ac35b09576b6/sensors-17-02215-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/ec80b2d94471/sensors-17-02215-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/343d78a1ae6c/sensors-17-02215-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/f9dfa798f93f/sensors-17-02215-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/d8f4a511dab0/sensors-17-02215-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/e0f50001c604/sensors-17-02215-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/037cfc364448/sensors-17-02215-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/12b1e50efb28/sensors-17-02215-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/ac35b09576b6/sensors-17-02215-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/ec80b2d94471/sensors-17-02215-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/343d78a1ae6c/sensors-17-02215-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/f9dfa798f93f/sensors-17-02215-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/d8f4a511dab0/sensors-17-02215-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/e0f50001c604/sensors-17-02215-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/037cfc364448/sensors-17-02215-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/12b1e50efb28/sensors-17-02215-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa7/5676671/ac35b09576b6/sensors-17-02215-g008.jpg

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本文引用的文献

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Sensors (Basel). 2017 Jun 1;17(6):1258. doi: 10.3390/s17061258.
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Adaptive Data Aggregation and Compression to Improve Energy Utilization in Solar-Powered Wireless Sensor Networks.自适应数据聚合与压缩以提高太阳能无线传感器网络中的能源利用效率
Sensors (Basel). 2017 May 27;17(6):1226. doi: 10.3390/s17061226.
3
Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks.基于马尔可夫链模型的无线传感器网络最优簇头选择
Sensors (Basel). 2017 Feb 23;17(3):440. doi: 10.3390/s17030440.