Adaptive distributed source coding for wireless sensor networks

Z. Tang, I.A. Glover, A. Evans, D. Monro, J. He

Research output: Contribution to conferencePaper

Abstract

It has been proven in theory that distributed source coding (DSC) can be used to compress correlated signals with or without loss. Recently this coding method has been used for the application of remote signal estimation in wireless sensor networks (WSN), where multiple sensor nodes compress their correlated observations without inter-node communications. Energy and bandwidth are therefore efficiently saved. No practical DSC scheme for WSNs, however, has been reported in the literature. In this paper, we study the problem of remote source estimation in WSN using a random-binning based DSC scheme. We analyze the impact of observation noise, quantization distortion, DSC decoding errors and network packet losses on the quality of the estimated signal. An adaptive control scheme is proposed to adapt the coding and transmission parameters to the network conditions. Simulation results show the proposed scheme both saves bandwidth and improves the quality of the source estimation.
LanguageEnglish
Number of pages6
Publication statusPublished - Apr 2006
Event Wireless Conference 2006 - Athens, Greece
Duration: 2 Apr 20065 Apr 2006

Conference

Conference Wireless Conference 2006
CountryGreece
CityAthens
Period2/04/065/04/06

Fingerprint

Wireless sensor networks
Bandwidth
Packet loss
Sensor nodes
Decoding
Communication

Keywords

  • artificial neural networks
  • adaptive
  • distributed source coding
  • wireless sensor networks

Cite this

Tang, Z., Glover, I. A., Evans, A., Monro, D., & He, J. (2006). Adaptive distributed source coding for wireless sensor networks. Paper presented at Wireless Conference 2006 , Athens, Greece.
Tang, Z. ; Glover, I.A. ; Evans, A. ; Monro, D. ; He, J. / Adaptive distributed source coding for wireless sensor networks. Paper presented at Wireless Conference 2006 , Athens, Greece.6 p.
@conference{610c9191752e4947be1b964a34f62e3b,
title = "Adaptive distributed source coding for wireless sensor networks",
abstract = "It has been proven in theory that distributed source coding (DSC) can be used to compress correlated signals with or without loss. Recently this coding method has been used for the application of remote signal estimation in wireless sensor networks (WSN), where multiple sensor nodes compress their correlated observations without inter-node communications. Energy and bandwidth are therefore efficiently saved. No practical DSC scheme for WSNs, however, has been reported in the literature. In this paper, we study the problem of remote source estimation in WSN using a random-binning based DSC scheme. We analyze the impact of observation noise, quantization distortion, DSC decoding errors and network packet losses on the quality of the estimated signal. An adaptive control scheme is proposed to adapt the coding and transmission parameters to the network conditions. Simulation results show the proposed scheme both saves bandwidth and improves the quality of the source estimation.",
keywords = "artificial neural networks , adaptive, distributed source coding, wireless sensor networks",
author = "Z. Tang and I.A. Glover and A. Evans and D. Monro and J. He",
year = "2006",
month = "4",
language = "English",
note = "Wireless Conference 2006 ; Conference date: 02-04-2006 Through 05-04-2006",

}

Tang, Z, Glover, IA, Evans, A, Monro, D & He, J 2006, 'Adaptive distributed source coding for wireless sensor networks' Paper presented at Wireless Conference 2006 , Athens, Greece, 2/04/06 - 5/04/06, .

Adaptive distributed source coding for wireless sensor networks. / Tang, Z.; Glover, I.A.; Evans, A.; Monro, D.; He, J.

2006. Paper presented at Wireless Conference 2006 , Athens, Greece.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Adaptive distributed source coding for wireless sensor networks

AU - Tang, Z.

AU - Glover, I.A.

AU - Evans, A.

AU - Monro, D.

AU - He, J.

PY - 2006/4

Y1 - 2006/4

N2 - It has been proven in theory that distributed source coding (DSC) can be used to compress correlated signals with or without loss. Recently this coding method has been used for the application of remote signal estimation in wireless sensor networks (WSN), where multiple sensor nodes compress their correlated observations without inter-node communications. Energy and bandwidth are therefore efficiently saved. No practical DSC scheme for WSNs, however, has been reported in the literature. In this paper, we study the problem of remote source estimation in WSN using a random-binning based DSC scheme. We analyze the impact of observation noise, quantization distortion, DSC decoding errors and network packet losses on the quality of the estimated signal. An adaptive control scheme is proposed to adapt the coding and transmission parameters to the network conditions. Simulation results show the proposed scheme both saves bandwidth and improves the quality of the source estimation.

AB - It has been proven in theory that distributed source coding (DSC) can be used to compress correlated signals with or without loss. Recently this coding method has been used for the application of remote signal estimation in wireless sensor networks (WSN), where multiple sensor nodes compress their correlated observations without inter-node communications. Energy and bandwidth are therefore efficiently saved. No practical DSC scheme for WSNs, however, has been reported in the literature. In this paper, we study the problem of remote source estimation in WSN using a random-binning based DSC scheme. We analyze the impact of observation noise, quantization distortion, DSC decoding errors and network packet losses on the quality of the estimated signal. An adaptive control scheme is proposed to adapt the coding and transmission parameters to the network conditions. Simulation results show the proposed scheme both saves bandwidth and improves the quality of the source estimation.

KW - artificial neural networks

KW - adaptive

KW - distributed source coding

KW - wireless sensor networks

M3 - Paper

ER -

Tang Z, Glover IA, Evans A, Monro D, He J. Adaptive distributed source coding for wireless sensor networks. 2006. Paper presented at Wireless Conference 2006 , Athens, Greece.