### Abstract

Existing maximum-likelihood sequence estimation (MLSE) schemes for channels with memory, resulting in intersymbol interference (ISI), have typically been implemented using the Viterbi algorithm (VA). For memoryless modulation schemes the resulting search complexity is O(M^{L}), where M is the alphabet size and L is the length of the ISI span in channel signaling intervals. This complexity renders the VA impractical for large M and/or L. In this paper we describe the structure and properties of a novel reduced-complexity iterative MLSE scheme based upon the expectation-maximization (EM) algorithm. This reduced-complexity iterative MLSE scheme is shown to have complexity O(LM) at each iteration. The approach provides an attractive alternative to the VA for large signaling alphabets and/or ISI span.

Original language | English |
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Title of host publication | Proceedings of the 1993 IEEE International Symposium on Information Theory |

Place of Publication | Piscataway, NJ, United States |

Publisher | Publ by IEEE |

ISBN (Print) | 0780308786 |

State | Published - Jan 1 1993 |

Event | Proceedings of the 1993 IEEE International Symposium on Information Theory - San Antonio, TX, USA Duration: Jan 17 1993 → Jan 22 1993 |

### Other

Other | Proceedings of the 1993 IEEE International Symposium on Information Theory |
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City | San Antonio, TX, USA |

Period | 1/17/93 → 1/22/93 |

### Fingerprint

### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*Proceedings of the 1993 IEEE International Symposium on Information Theory*Piscataway, NJ, United States: Publ by IEEE.

**Reduced-complexity iterative maximum-likelihood sequence estimation on channels with memory.** / Modestino, J. W.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the 1993 IEEE International Symposium on Information Theory.*Publ by IEEE, Piscataway, NJ, United States, Proceedings of the 1993 IEEE International Symposium on Information Theory, San Antonio, TX, USA, 1/17/93.

}

TY - GEN

T1 - Reduced-complexity iterative maximum-likelihood sequence estimation on channels with memory

AU - Modestino, J. W.

PY - 1993/1/1

Y1 - 1993/1/1

N2 - Existing maximum-likelihood sequence estimation (MLSE) schemes for channels with memory, resulting in intersymbol interference (ISI), have typically been implemented using the Viterbi algorithm (VA). For memoryless modulation schemes the resulting search complexity is O(ML), where M is the alphabet size and L is the length of the ISI span in channel signaling intervals. This complexity renders the VA impractical for large M and/or L. In this paper we describe the structure and properties of a novel reduced-complexity iterative MLSE scheme based upon the expectation-maximization (EM) algorithm. This reduced-complexity iterative MLSE scheme is shown to have complexity O(LM) at each iteration. The approach provides an attractive alternative to the VA for large signaling alphabets and/or ISI span.

AB - Existing maximum-likelihood sequence estimation (MLSE) schemes for channels with memory, resulting in intersymbol interference (ISI), have typically been implemented using the Viterbi algorithm (VA). For memoryless modulation schemes the resulting search complexity is O(ML), where M is the alphabet size and L is the length of the ISI span in channel signaling intervals. This complexity renders the VA impractical for large M and/or L. In this paper we describe the structure and properties of a novel reduced-complexity iterative MLSE scheme based upon the expectation-maximization (EM) algorithm. This reduced-complexity iterative MLSE scheme is shown to have complexity O(LM) at each iteration. The approach provides an attractive alternative to the VA for large signaling alphabets and/or ISI span.

UR - http://www.scopus.com/inward/record.url?scp=0027191646&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0027191646&partnerID=8YFLogxK

M3 - Conference contribution

SN - 0780308786

BT - Proceedings of the 1993 IEEE International Symposium on Information Theory

PB - Publ by IEEE

CY - Piscataway, NJ, United States

ER -