Title :
Low Complexity SNR Estimation for Transmissions Over Time-Varying Flat-Fading Channels
Author :
Morelli, M. ; Moretti, M. ; Imbarlina, G. ; Dimitriou, N.
Author_Institution :
Dipt. di Ing. dell´Inf., Univ. of Pisa, Pisa
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.
Keywords :
fading channels; maximum likelihood estimation; polynomial approximation; SNR estimation; maximum likelihood estimator; noise variance; polynomial approximation; signal correlation matrix; signal power; subspace decomposition approach; time-varying flat-fading channels; Approximation algorithms; Diversity reception; Matrix decomposition; Maximum likelihood estimation; Multiaccess communication; OFDM; Phase shift keying; Polynomials; Signal to noise ratio; Time-varying channels;
Conference_Titel :
Wireless Communications and Networking Conference, 2009. WCNC 2009. IEEE
Conference_Location :
Budapest
Print_ISBN :
978-1-4244-2947-9
DOI :
10.1109/WCNC.2009.4917794
