Energy-Efficient Over-the-Air Computation Scheme for Densely Deployed IoT Networks

Semiha Tedik Basaran*, Gunes Karabulut Kurt, Periklis Chatzimisios

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

In this article, we propose a spatial sampling approach to reduce energy consumption for over-the-air (function) computation (AirComp) scheme by utilizing the cross-correlations among sensor readings. Since the conventional AirComp scheme leads to a reduction in total transmission time and latency thanks to the joint communication and computation processes, it is especially well-suited to Internet of Things (IoT) monitoring systems. AirComp lets simultaneous transmissions of all nodes by exploiting the superposition property of wireless channel; however, it does not overcome the high energy consumption paradigm, which is a fundamental problem of densely deployed IoT monitoring systems. We present a minimum mean square error (MMSE) estimation scheme while a small number of observations are available for densely deployed networks. The proposed MMSE estimator provides a significant mean squared error improvement with reducing energy consumption compared to the conventional estimator. Since the network lifetime of IoT monitoring systems can be almost doubled, the proposed estimator provides flexibility for the dense deployment of nodes. The simulation results verify the theoretical expressions.

Original languageEnglish
Article number8818333
Pages (from-to)3558-3565
Number of pages8
JournalIEEE Transactions on Industrial Informatics
Volume16
Issue number5
DOIs
Publication statusPublished - May 2020

Bibliographical note

Publisher Copyright:
© 2005-2012 IEEE.

Keywords

  • Function computation
  • Internet of Things (IoT)
  • over-the-air computation

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