Improving energy efficiency in a wireless sensor network by combining cooperative MIMO with data aggregation

Qiang Gao, Yi Zuo, Jun Zhang, Xiao-Hong Peng

Research output: Contribution to journalArticlepeer-review

Abstract

In wireless sensor networks where nodes are powered by batteries, it is critical to prolong the network lifetime by minimizing the energy consumption of each node. In this paper, the cooperative multiple-input-multiple-output (MIMO) and data-aggregation techniques are jointly adopted to reduce the energy consumption per bit in wireless sensor networks by reducing the amount of data for transmission and better using network resources through cooperative communication. For this purpose, we derive a new energy model that considers the correlation between data generated by nodes and the distance between them for a cluster-based sensor network by employing the combined techniques. Using this model, the effect of the cluster size on the average energy consumption per node can be analyzed. It is shown that the energy efficiency of the network can significantly be enhanced in cooperative MIMO systems with data aggregation, compared with either cooperative MIMO systems without data aggregation or data-aggregation systems without cooperative MIMO, if sensor nodes are properly clusterized. Both centralized and distributed data-aggregation schemes for the cooperating nodes to exchange and compress their data are also proposed and appraised, which lead to diverse impacts of data correlation on the energy performance of the integrated cooperative MIMO and data-aggregation systems.
Original languageEnglish
Pages (from-to)3956-3965
Number of pages10
JournalIEEE Transactions on Vehicular Technology
Volume59
Issue number8
Early online date5 Aug 2010
DOIs
Publication statusPublished - Oct 2010

Bibliographical note

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Keywords

  • centralized data-aggregation scheme
  • cluster-based sensor network
  • cooperative MIMO
  • data aggregation
  • data compression
  • distributed data-aggregation scheme
  • energy consumption reduction
  • energy efficiency
  • wireless sensor network

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