A sequential Monte Carlo method for adaptive blind timing estimation and data detection

Accurate estimation of synchronization parameters is critical for reliable data detection in digital transmission. Although several techniques have been proposed in the literature for estimation of the reference parameters, i.e., timing, carrier phase, and carrier frequency offsets, they are based on either heuristic arguments or approximations, since optimal estimation is analytically intractable in most practical setups. In this paper, we introduce a new alternative approach for blind synchronization and data detection derived within the Bayesian framework and implemented via the sequential Monte Carlo (SMC) methodology. By considering an extended dynamic system where the reference parameters and the transmitted symbols are system-state variables, the proposed SMC technique guarantees asymptotically minimal symbol error rate when it is combined with adequate receiver architectures, both in open-loop and closed-loop configurations. The performance of the proposed technique is studied analytically, by deriving the posterior Cra/spl acute/mer-Rao bound for timing estimation and through computer simulations that illustrate the overall performance of the resulting receivers.