TY - JOUR
T1 - A Monte Carlo implementation of the SAGE algorithm for joint soft-multiuser decoding, channel parameter estimation, and code acquisition
AU - Kocian, Alexander
AU - Panayirci, Erdal
AU - Poor, H. Vincent
AU - Ruggieri, Marina
N1 - Funding Information:
Manuscript received March 18, 2010; accepted July 05, 2010. Date of publication July 29, 2010; date of current version October 13, 2010. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Huaiyu Dai. This work was supported in part by the U.S. National Science Foundation under Grant CNS-09-05398. The material in the paper was presented in part at the IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Perugia, Italy, June 2009.
PY - 2010/11
Y1 - 2010/11
N2 - This paper presents an iterative scheme for joint timing acquisition, multi-channel parameter estimation, and multiuser soft-data decoding. As an example, an asynchronous convolutionally coded direct-sequence code-division multiple-access system is considered. The proposed receiver is derived within the space-alternating generalized expectation-maximization framework, implying that 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.
AB - This paper presents an iterative scheme for joint timing acquisition, multi-channel parameter estimation, and multiuser soft-data decoding. As an example, an asynchronous convolutionally coded direct-sequence code-division multiple-access system is considered. The proposed receiver is derived within the space-alternating generalized expectation-maximization framework, implying that 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.
KW - Expectation maximization algorithms
KW - Monte Carlo mthods
KW - multiaccess communication
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U2 - 10.1109/TSP.2010.2062181
DO - 10.1109/TSP.2010.2062181
M3 - Article
AN - SCOPUS:79953815669
SN - 1053-587X
VL - 58
SP - 5756
EP - 5766
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 11
M1 - 5530415
ER -