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.

Low Complexity SNR Estimation for Transmissions over Time-Varying Flat-Fading Channels

MORELLI, MICHELE;MORETTI, MARCO;
2009-01-01

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.
2009
9781424429479
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/198163
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