Maximum likelihood sequence detection for OFDM transmissions over unknown multipath fading channels is a challenging task for lack of efficient methods to maximize the likelihood function. A feasible solution to this problem based on the Expectation-Maximization (EM) algorithm has been recently proposed in the context of space-time block-coded OFDM. The resulting detector operates iteratively and exploits knowledge of the channel statistics and the operating signal-to-noise ratio (SNR). In this work we address the problem of estimating the above quantities in a recursive fashion. Simulations indicate that the EM detector employing the estimated SNR and channel statistics has better performance than other existing schemes that operate in a mismatched mode. Also, the performance loss with respect to a system with perfect channel knowledge is negligible at SNR values of practical interest.

Estimation of Channel Statistics for Iterative Detection of OFDM Signals

MORELLI, MICHELE;SANGUINETTI, LUCA
2004

Abstract

Maximum likelihood sequence detection for OFDM transmissions over unknown multipath fading channels is a challenging task for lack of efficient methods to maximize the likelihood function. A feasible solution to this problem based on the Expectation-Maximization (EM) algorithm has been recently proposed in the context of space-time block-coded OFDM. The resulting detector operates iteratively and exploits knowledge of the channel statistics and the operating signal-to-noise ratio (SNR). In this work we address the problem of estimating the above quantities in a recursive fashion. Simulations indicate that the EM detector employing the estimated SNR and channel statistics has better performance than other existing schemes that operate in a mismatched mode. Also, the performance loss with respect to a system with perfect channel knowledge is negligible at SNR values of practical interest.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/192829
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 0
social impact