Code-aided Bayesian Parameter Estimation for Multi-Carrier Systems

In this paper, we present a theoretical framework for code-aided synchronization and channel estimation for multi-carrier (MC) systems. Our endeavor is to exploit all available information from the received signal for the estimation of the unknown parameters. By means of the Expectation-Maximization (EM) formalism, we will show how soft information of the coded symbols computed by the detector can be combined with pilot symbols in a systematic and efficient manner in order to improve the overall system performance. The resulting code-aided algorithm comes with a negligible increase in processing demands compared to its data-aided counterpart, since the synchronizer and the estimator can be embedded in the iterative ’turbo’ detector. For sake of simplicity, we develop our estimation framework for a simple orthogonal frequency division multiplexing (OFDM) transceiver. As far as the estimation is concerned, extension to other multi-carrier set-ups using more advanced detectors is conceptually very straightforward. Computer simulations show that the proposed algorithm outperforms the conventional data-aided estimation algorithms.