### Abstract

In this paper, we propose a new path metric, which improves the performance of soft-input soft-output (SISO) 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, called improved path metric, re.ect the contribution of unvisited paths using an unconstrained minimum mean squared error (MMSE) estimate of undecided symbols. The improved path metric is applied to SISO M-algorithm, which finds a list of symbol candidates based on breadth-first search strategy and computes a posteriori probability of each entry of the symbol vector. We study the probability of correct path loss (CPL) for the improved path metric and confirm the performance improvement over the conventional path metric.

Original language | English |
---|---|

Title of host publication | 2010 Information Theory and Applications Workshop, ITA 2010 - Conference Proceedings |

Pages | 59-63 |

Number of pages | 5 |

DOIs | |

State | Published - 2010 May 31 |

Event | 2010 Information Theory and Applications Workshop, ITA 2010 - San Diego, CA, United States Duration: 2010 Jan 31 → 2010 Feb 5 |

### Publication series

Name | 2010 Information Theory and Applications Workshop, ITA 2010 - Conference Proceedings |
---|

### Other

Other | 2010 Information Theory and Applications Workshop, ITA 2010 |
---|---|

Country | United States |

City | San Diego, CA |

Period | 10/01/31 → 10/02/5 |

### Cite this

*2010 Information Theory and Applications Workshop, ITA 2010 - Conference Proceedings*(pp. 59-63). [5454143] (2010 Information Theory and Applications Workshop, ITA 2010 - Conference Proceedings). https://doi.org/10.1109/ITA.2010.5454143