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

Alexander Kocian, Erdal Panayirci, H. Vincent Poor, Marina Ruggieri

Research output: Contribution to journalArticle

2 Scopus citations

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.

Original languageEnglish (US)
Article number5530415
Pages (from-to)5756-5766
Number of pages11
JournalIEEE Transactions on Signal Processing
Volume58
Issue number11
DOIs
StatePublished - Nov 1 2010

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • Expectation maximization algorithms
  • Monte Carlo mthods
  • multiaccess communication

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