### 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) |
---|---|

Title of host publication | 2008 Information Theory and Applications Workshop - Conference Proceedings, ITA |

Pages | 66-69 |

Number of pages | 4 |

DOIs | |

State | Published - Oct 6 2008 |

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

### Publication series

Name | 2008 Information Theory and Applications Workshop - Conference Proceedings, ITA |
---|

### Other

Other | 2008 Information Theory and Applications Workshop - ITA |
---|---|

Country | United States |

City | San Diego, CA |

Period | 1/27/08 → 2/1/08 |

### ASJC Scopus subject areas

- Computer Science Applications
- Information Systems

## Fingerprint Dive into the research topics of 'A note on convergence rate of constrained capacity estimation algorithms over ISI channels'. Together they form a unique fingerprint.

## Cite this

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