Linear estimate-based look-ahead path metric for efficient soft-input soft-output tree detection

Jun Won Choi, Byonghyo Shim, Andrew Carl Singer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a new path metric, which improves performance of soft-input soft-output tree detection for iterative detection and decoding (IDD) systems. While the conventional path metric accounts for the contribution of symbols on a visited path due to the causal nature of tree search, the new path metric reflect the contribution of unvisited paths using an unconstrained soft estimate of undecided symbols. This path metric, referred to as a linear estimate-based look-ahead (LE-LA) path metric is applied to a soft-input soft-output M-algorithm that finds a list of promising symbol candidates and computes a posteriori probability of each entry of the symbol vector using the candidate list found. Through the analysis of a probability of correct path loss (CPL) and computer simulations, we show performance gain of the LE-LA path metric over the conventional path metric.

Original languageEnglish (US)
Title of host publication2010 IEEE International Symposium on Information Theory, ISIT 2010 - Proceedings
Pages804-808
Number of pages5
DOIs
StatePublished - Aug 23 2010
Event2010 IEEE International Symposium on Information Theory, ISIT 2010 - Austin, TX, United States
Duration: Jun 13 2010Jun 18 2010

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8103

Other

Other2010 IEEE International Symposium on Information Theory, ISIT 2010
CountryUnited States
CityAustin, TX
Period6/13/106/18/10

ASJC Scopus subject areas

  • Applied Mathematics
  • Modeling and Simulation
  • Theoretical Computer Science
  • Information Systems

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    Choi, J. W., Shim, B., & Singer, A. C. (2010). Linear estimate-based look-ahead path metric for efficient soft-input soft-output tree detection. In 2010 IEEE International Symposium on Information Theory, ISIT 2010 - Proceedings (pp. 804-808). [5513641] (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.2010.5513641