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Circuits, Systems, and Signal Processing

, Volume 33, Issue 8, pp 2605–2623 | Cite as

Detection of Channel Variations to Improve Channel Estimation Methods

  • Adriana Dapena
  • José A. García-NayaEmail author
  • Paula M. Castro
  • Vicente Zarzoso
Article
  • 166 Downloads

Abstract

In current digital communication systems, channel information is typically acquired by supervised approaches that use pilot symbols included in the transmit frames. Given that pilot symbols do not convey user data, they penalize throughput spectral efficiency, and transmit energy consumption of the system. Unsupervised channel estimation algorithms could be used to mitigate the aforementioned drawbacks although they present higher computational complexity than that offered by supervised ones. This paper proposes a simple decision method suitable for slowly varying channels to determine whether the channel has suffered a significant variation, which requires to estimate the matrix of the recently changed channel. Otherwise, a previous estimate is used to recover the transmitted symbols. The main advantage of this method is that the decision criterion is only based on information acquired during the time frame synchronization, which is carried out at the receiver. We show that the proposed criterion provides a considerable improvement of computational complexity for both supervised and unsupervised methods, without incurring in a penalization in terms of symbol error ratio. Specifically, we consider systems that make use of the popular Alamouti code. Performance evaluation is accomplished by means of simulated channels as well as making use of indoor wireless channels measured using a testbed.

Keywords

Channel estimation Supervised approach Unsupervised approach Alamouti code 

Notes

Acknowledgments

This work has been funded by Xunta de Galicia, Ministerio de Ciencia e Innovación of Spain, and FEDER funds of the European Union under Grants with Nos. 2012/287, TEC2010-19545-C04-01, and CSD2008-00010.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Adriana Dapena
    • 1
  • José A. García-Naya
    • 1
    Email author
  • Paula M. Castro
    • 1
  • Vicente Zarzoso
    • 2
  1. 1.Group of Electronic Technology and CommunicationsDepartment of Electronics and Systems, Faculty of Informatics, University of A CoruñaA CoruñaSpain
  2. 2.I3S Laboratory, CNRSUniversity of Nice Sophia AntipolisSophia Antipolis CedexFrance

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