A sequential Monte Carlo technique for blind synchronization and detection in frequency-flat Rayleigh fading wireless channels

This paper is aimed at the derivation of adaptive signal processing algorithms that jointly perform the tasks of blind data detection and generalized synchronization in a digital receiver. Optimal recovery of the synchronization parameters (timing, phase and frequency offsets) is analytically intractable and, as a consequence, most existing synchronization methods are either heuristic or based on approximate maximum likelihood (ML) arguments. We herein introduce an alternative approach derived within a Bayesian estimation framework and implemented via the sequential Monte Carlo (SMC) methodology. The algorithm is derived by considering an extended dynamic system where the reference parameters and the transmitted symbols are system-state random processes. The proposed model is well suited to represent frequency-flat fast-fading wireless channels. We also suggest two possible configurations for the receiver architecture that, combined with the proposed SMC technique, guarantee the achievement of asymptotically minimal symbol error rate (SER). The performance of the proposed technique is studied both analytically, by deriving the posterio Cramér-Rao bound (PCRB) for timing estimation, and through computer simulations that illustrate the accuracy of synchronization and the overall performance of the resulting blind receiver in terms of its SER.