A Monte Carlo Implementation of the Sage Algorithm for Joint Soft-Multiuser Decoding Channel Parameter Estimation and Code Acquisition

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Date

2010

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Yes

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Abstract

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. © 2006 IEEE.

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Keywords

Expectation maximization algorithms, Monte Carlo mthods, Multiaccess communication, multiaccess communication, Expectation maximization algorithms; multiaccess communication; Monte Carlo mthods, Expectation maximization algorithms, Monte Carlo mthods, Settore ING-INF/03 - TELECOMUNICAZIONI, Multiaccess communication, Monte Carlo methods, 003

Turkish CoHE Thesis Center URL

Fields of Science

0508 media and communications, 05 social sciences, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

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WoS Q

Q1

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Q1
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OpenCitations Citation Count
2

Source

IEEE Transactions on Signal Processing

Volume

58

Issue

11

Start Page

5756

End Page

5766
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2

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7

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142

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