Cart (Loading....) | Create Account
Close category search window

Signal-Processing-Aided Distributed Compression in Virtual MIMO-Based 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

3 Author(s)
Jayaweera, S.K. ; New Mexico Univ., Albuquerque ; Chebolu, M.L. ; Donapati, R.K.

An adaptive signal-processing-aided distributed source coding scheme for virtual multiple-input-multiple-output communication-based wireless sensor networks (WSNs) is proposed. A computationally inexpensive distributed compression scheme that exploits the spatiotemporal correlations of sensor data is implemented with the aid of a recursive least squares (RLS)-based adaptive correlation tracking algorithm. The tracked correlation is used to compute side information that assists in distributed source compression. The proposed virtual space-time block coding and RLS-based compression side information are shown to improve energy efficiency at distributed nodes compared to previously proposed schemes with single-input-single-output communication. A semi-analytical approach is developed for energy efficiency analysis over different channel conditions and transmission distances. The energy efficiency performance of the proposed design is evaluated on real WSN data. The results show that the proposed integrated system outperforms conventional designs beyond certain transmission distance thresholds and leads to lower decoding errors, which makes it a good candidate for energy-aware WSNs.

Published in:

Vehicular Technology, IEEE Transactions on  (Volume:56 ,  Issue: 5 )

Date of Publication:

Sept. 2007

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.