The paper presents an iterative scheme for joint timing acquisition, multi-channel parameter estimation, and multiuser soft-data decoding. As an example we consider an asynchronous convolutionally coded direct-sequence code-division multiple-access system. The proposed receiver is derived within the space-alternating generalized expectation-maximization framework, implying the convergence in likelihood is guaranteed under appropriate conditions in contrast to many other iterative receiver architectures. The proposed receiver iterates between joint posterior data estimation, interference cancellation, and single-user channel estimation and timing acquisition. A Markov Chain Monte Carlo technique, namely Gibbs sampling, is employed to compute the a posteriori probabilities of data symbols in a computationally efficient way. Computer simulations in flat Rayleigh fading show that the proposed algorithm is able to handle high system loads unlike many other iterative receivers.

Kocian, A., Panayirci, E., Poor, H., Ruggieri, M. (2010). A Monte Carlo implementation of the SAGE algorithm for joint soft-multiuser decoding, channel parameter estimation, and code acquisition. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 58(11), 5756-5766 [10.1109/TSP.2010.2062181].

A Monte Carlo implementation of the SAGE algorithm for joint soft-multiuser decoding, channel parameter estimation, and code acquisition

RUGGIERI, MARINA
2010-01-01

Abstract

The paper presents an iterative scheme for joint timing acquisition, multi-channel parameter estimation, and multiuser soft-data decoding. As an example we consider an asynchronous convolutionally coded direct-sequence code-division multiple-access system. The proposed receiver is derived within the space-alternating generalized expectation-maximization framework, implying the convergence in likelihood is guaranteed under appropriate conditions in contrast to many other iterative receiver architectures. The proposed receiver iterates between joint posterior data estimation, interference cancellation, and single-user channel estimation and timing acquisition. A Markov Chain Monte Carlo technique, namely Gibbs sampling, is employed to compute the a posteriori probabilities of data symbols in a computationally efficient way. Computer simulations in flat Rayleigh fading show that the proposed algorithm is able to handle high system loads unlike many other iterative receivers.
2010
Pubblicato
Rilevanza internazionale
Articolo
Sì, ma tipo non specificato
Settore ING-INF/03 - TELECOMUNICAZIONI
English
Con Impact Factor ISI
Expectation maximization algorithms, multiaccess communication, Monte Carlo methods
Il paper è frutto di una collaborazione internazionale
Kocian, A., Panayirci, E., Poor, H., Ruggieri, M. (2010). A Monte Carlo implementation of the SAGE algorithm for joint soft-multiuser decoding, channel parameter estimation, and code acquisition. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 58(11), 5756-5766 [10.1109/TSP.2010.2062181].
Kocian, A; Panayirci, E; Poor, H; Ruggieri, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/10468
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