Discrete Random Signals and Statistical Signal Processing
Discrete Random Signals and Statistical Signal Processing
On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Joint Data and Kalman Estimation for Rayleigh Fading Channels
Wireless Personal Communications: An International Journal
EURASIP Journal on Applied Signal Processing
Channel tracking using particle filtering in unresolvable multipath environments
EURASIP Journal on Applied Signal Processing
Posterior Cramer-Rao bounds for discrete-time nonlinear filtering
IEEE Transactions on Signal Processing
A survey of convergence results on particle filtering methods forpractitioners
IEEE Transactions on Signal Processing
Conditional maximum likelihood timing recovery: estimators andbounds
IEEE Transactions on Signal Processing
Multi-input multi-output fading channel tracking and equalizationusing Kalman estimation
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Adaptive joint detection and decoding in flat-fading channels via mixture Kalman filtering
IEEE Transactions on Information Theory
A particle filter for frequency synchronization in MIMO-OFDM systems
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
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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 posterior 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.