### Abstract

It has recently become popular to use simulation-based algorithms to empirically estimate achievable information rates over intersymbol interference (ISI) channels with inputs from specific input constellations. Such algorithms are guaranteed to converge by invoking the Shannon-McMillan-Brieman theorem provided that the output sequence is stationary and ergodic. In this note, we establish a central limit theorem result on the rate of convergence, and show that the variance of the estimates decreases like 1/N (where N is the sequence length employed) as N goes to infinity. This result indicates that it is possible to achieve estimation accuracy with any desired level by simply increasing the number of samples appropriately.

Original language | English (US) |
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Title of host publication | 2008 Information Theory and Applications Workshop - Conference Proceedings, ITA |

Pages | 66-69 |

Number of pages | 4 |

DOIs | |

State | Published - 2008 |

Event | 2008 Information Theory and Applications Workshop - ITA - San Diego, CA, United States Duration: Jan 27 2008 → Feb 1 2008 |

### Other

Other | 2008 Information Theory and Applications Workshop - ITA |
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Country | United States |

City | San Diego, CA |

Period | 1/27/08 → 2/1/08 |

### Fingerprint

### ASJC Scopus subject areas

- Computer Science Applications
- Information Systems

### Cite this

*2008 Information Theory and Applications Workshop - Conference Proceedings, ITA*(pp. 66-69). [4601026] https://doi.org/10.1109/ITA.2008.4601026

**A note on convergence rate of constrained capacity estimation algorithms over ISI channels.** / Duman, Tolga M.; Zhang, Junshan.

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

*2008 Information Theory and Applications Workshop - Conference Proceedings, ITA.*, 4601026, pp. 66-69, 2008 Information Theory and Applications Workshop - ITA, San Diego, CA, United States, 1/27/08. https://doi.org/10.1109/ITA.2008.4601026

}

TY - GEN

T1 - A note on convergence rate of constrained capacity estimation algorithms over ISI channels

AU - Duman, Tolga M.

AU - Zhang, Junshan

PY - 2008

Y1 - 2008

N2 - It has recently become popular to use simulation-based algorithms to empirically estimate achievable information rates over intersymbol interference (ISI) channels with inputs from specific input constellations. Such algorithms are guaranteed to converge by invoking the Shannon-McMillan-Brieman theorem provided that the output sequence is stationary and ergodic. In this note, we establish a central limit theorem result on the rate of convergence, and show that the variance of the estimates decreases like 1/N (where N is the sequence length employed) as N goes to infinity. This result indicates that it is possible to achieve estimation accuracy with any desired level by simply increasing the number of samples appropriately.

AB - It has recently become popular to use simulation-based algorithms to empirically estimate achievable information rates over intersymbol interference (ISI) channels with inputs from specific input constellations. Such algorithms are guaranteed to converge by invoking the Shannon-McMillan-Brieman theorem provided that the output sequence is stationary and ergodic. In this note, we establish a central limit theorem result on the rate of convergence, and show that the variance of the estimates decreases like 1/N (where N is the sequence length employed) as N goes to infinity. This result indicates that it is possible to achieve estimation accuracy with any desired level by simply increasing the number of samples appropriately.

UR - http://www.scopus.com/inward/record.url?scp=52949088662&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=52949088662&partnerID=8YFLogxK

U2 - 10.1109/ITA.2008.4601026

DO - 10.1109/ITA.2008.4601026

M3 - Conference contribution

AN - SCOPUS:52949088662

SN - 1424426707

SN - 9781424426706

SP - 66

EP - 69

BT - 2008 Information Theory and Applications Workshop - Conference Proceedings, ITA

ER -