Energy-Efficient Data Acquisition in Wireless Sensor Networks Using Compressed Sensing
Energy-Efficient Data Acquisition in Wireless Sensor Networks Using Compressed Sensing
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DOI：
10.1109/dcc.2011.29
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发表时间：
2011-03
期刊：
影响因子：
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通讯作者：
Mina Sartipi;R. Fletcher
中科院分区：
文献类型：
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作者：
Mina Sartipi;R. Fletcher
本文研究了无线传感器网络中的数据采集问题。最近恢复活力的压缩传感(CS)技术提出了一种以低于奈奎斯特的速率捕获稀疏信号的新方法。将现有的CS算法直接应用于无线传感器网络存在缺陷，这主要是由于CS需要大量的交互通信来生成每个投影。为了缓解这些缺点，我们提出了使用随机游走的压缩分布式感知(CDS(RW))，这是一种在无线传感器网络中使用无速率编码的CS的算法。该算法与路由算法和网络拓扑无关。CDS(RW)收集足够数量的传感器读数，同时将它们组合在一起，而不会显著增加内部通信成本。对于一组并行信道，我们用码设计来模拟CS问题，这有助于我们设计码率较低的码度分布。该模型提供了使用非均匀和不等差错保护码的优点。
In this paper, we study the problem of data acquisition in wireless sensor networks (WSNs). A recently revitalized technique called compressive sensing (CS) has presented a new method to capture sparse signals at a rate below Nyquist. There are drawbacks to directly applying the existing CS algorithm to WSNs, which are mainly due to the fact that CS requires a large number of inter-communications for generating each projection. To mitigate these drawbacks, we propose compressive distributed sensing using random walk (CDS(RW)), an algorithm for CS in WSNs that uses rate less coding. This algorithm is independent of routing algorithms and network topologies. CDS(RW) collects sufficient number of sensor readings while combining them together without significantly increasing the inter-communication cost. We model the CS problem with code design for a set of parallel channels which helps us to design the rate less code degree distribution. This model provides the advantage of using non-uniform and unequal error protection codes.