A Coding Theorem for Multiterminal Estimation

Author

Zia, Amin ; Reilly, James P. ; Field, Timothy R. ; Shirani, Shahram

Author_Institution

Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, Ont.

Volume

4

fYear

2006

fDate

14-19 May 2006

Abstract

In this paper a coding theorem for multiterminal estimation is presented. The theorem is a generalization of the distributed coding theorem first proved by Slepian and Wolf (1973), where the goal is to estimate the joint probability distribution of correlated sources, rather than to reconstruct them at the receiver. For this, it is shown first that the joint-type of the received sequences is a sufficient statistic for estimation. Then, it is proved that for sufficiently large sequences, only a sum-rate lower bounded by the mutual information of the correlated sources is "sufficient" to perfectly reconstruct the sufficient statistic at the receiver. Simulation results for the special case of estimation with side information at the receiver is provided

Keywords

encoding; receivers; statistical distributions; correlated sources; distributed coding theorem; multiterminal estimation; probability distribution; receiver; Capacitive sensors; Codes; Communication channels; Estimation theory; Mutual information; Parameter estimation; Probability distribution; Sensor phenomena and characterization; Source coding; Statistical distributions;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on

Conference_Location

Toulouse

ISSN

1520-6149

Print_ISBN

1-4244-0469-X

Type

conf

DOI

10.1109/ICASSP.2006.1661064

Filename

1661064