In this paper we consider the problem of data-aided synchronization in the up-link of a multiple access (MA) orthogonal frequency division multiplexing (OFDM) system based on offset quadrature amplitude modulation (OQAM). In particular, the joint maximum-likelihood (ML) phase offset and symbol timing estimator exploiting a short known preamble embedded in the burst received from each of U users is derived. Since the waveforms of the different users are nearly orthogonal, the ML approach leads to U different joint phase offset and symbol timing estimators.Moreover, for each user the phase estimate is in closed form, and, then, the symbol timing estimator requires only an one-dimensional maximization procedure. The performance of the proposed ML estimator is assessed via computer simulations both in AWGN and multipath channel, and for three different allocation schemes.
Data-aided symbol timing estimation for multiple-access OFDM/OQAM systems / Fusco, Tilde; Petrella, Angelo; Tanda, Mario. - ELETTRONICO. - (2009), pp. 1-5. (Intervento presentato al convegno International Conference on Communications (ICC 2009) tenutosi a Dresden (Germany) nel June 14-18) [10.1109/ICC.2009.5198880].
Data-aided symbol timing estimation for multiple-access OFDM/OQAM systems
FUSCO, TILDE;PETRELLA, ANGELO;TANDA, MARIO
2009
Abstract
In this paper we consider the problem of data-aided synchronization in the up-link of a multiple access (MA) orthogonal frequency division multiplexing (OFDM) system based on offset quadrature amplitude modulation (OQAM). In particular, the joint maximum-likelihood (ML) phase offset and symbol timing estimator exploiting a short known preamble embedded in the burst received from each of U users is derived. Since the waveforms of the different users are nearly orthogonal, the ML approach leads to U different joint phase offset and symbol timing estimators.Moreover, for each user the phase estimate is in closed form, and, then, the symbol timing estimator requires only an one-dimensional maximization procedure. The performance of the proposed ML estimator is assessed via computer simulations both in AWGN and multipath channel, and for three different allocation schemes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.