By Topic

Distributed Incremental Quantization and Estimation for Wireless Sensor Networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)

This paper proposes a distributed incremental quantization and estimation scheme by which each sensor can make a maximum likelihood estimation (MLE) of the unknown parameter based on its local observations and the quantized messages transmitted by the previous sensor. We derive the upper bound of the estimation mean squared error (MSE) of the proposed scheme, and propose the bit allocation algorithms, which minimize the total required bandwidth while ensuring a given MSE performance. Simulation results demonstrate that the proposed scheme requires much less bandwidth, but achieves around 40% MSE reduction compared with the distributed adaptive quantization and estimation scheme.

Published in:

Vehicular Technology Conference, 2008. VTC 2008-Fall. IEEE 68th

Date of Conference:

21-24 Sept. 2008