Low complexity SNR estimation for transmissions over time-varying flat-fading channels

  • Authors:

  • Michele Morelli;Marco Moretti;Giuseppe Imbarlina;Nikos Dimitriou

  • Affiliations:

  • Dipartimento di Ingegneria dell'Informazione, University of Pisa, Italy;Dipartimento di Ingegneria dell'Informazione, University of Pisa, Italy;Dipartimento di Ingegneria dell'Informazione, University of Pisa, Italy;NKUA, IASA, Greece

  • Venue:
  • WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
  • Year:
  • 2009

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Abstract

In this paper we present two algorithms for SNR estimation for transmissions over flat-fading time-varying channels. The first method exploits a polynomial approximation of the time-varying channel to derive a joint maximum likelihood estimator of the signal power and noise variance. The second technique is based on a subspace decomposition approach and exploits the inherent properties of the signal correlation matrix. Both algorithms can be implemented with affordable complexity and exhibit excellent performance.