Integrated source-channel decoding for correlated data-gathering sensor networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

This paper explores integrated source-channel decoding, driven by wireless sensor network applications where correlated information acquired by the network is gathered at a destination node. The collection of coded measurements sent to the destination, called a source-channel product codeword, has redundancy due to both correlation of the measurements and the channel code used for each measurement. At the destination, source-channel (SC) decoding of this code combines decoding using (i) the deterministic structure of the channel-coded individual measurements and (ii) the probabilistic structure of a prior model, called the global model, that describes the correlation structure of the SC product codewords. We demonstrate the utility of SC decoding via MAP SC decoding experiments using a (7,4,3) Hamming code and a Gaussian global model. We also show that SC decoding can exploit even the simplest possible code, a single-parity check code, using a MAP SC decoder that integrates the parity check constraint and global model. We describe the design of a low-complexity message-passing decoder and show it can improve performance in the poor-quality channels often found in multi-hop wireless data-gathering sensor networks.

Original languageEnglish (US)
Title of host publicationIEEE Wireless Communications and Networking Conference, WCNC
Pages1261-1266
Number of pages6
StatePublished - 2008
EventIEEE Wireless Communications and Networking Conference, WCNC 2008 - Las Vegas, NV, United States
Duration: Mar 31 2008Apr 3 2008

Other

OtherIEEE Wireless Communications and Networking Conference, WCNC 2008
CountryUnited States
CityLas Vegas, NV
Period3/31/084/3/08

Fingerprint

Sensor networks
Decoding
Message passing
Redundancy
Wireless sensor networks
Experiments

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Howard, S. L., & Flikkema, P. G. (2008). Integrated source-channel decoding for correlated data-gathering sensor networks. In IEEE Wireless Communications and Networking Conference, WCNC (pp. 1261-1266). [4489258]

Integrated source-channel decoding for correlated data-gathering sensor networks. / Howard, Sheryl L; Flikkema, Paul G.

IEEE Wireless Communications and Networking Conference, WCNC. 2008. p. 1261-1266 4489258.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Howard, SL & Flikkema, PG 2008, Integrated source-channel decoding for correlated data-gathering sensor networks. in IEEE Wireless Communications and Networking Conference, WCNC., 4489258, pp. 1261-1266, IEEE Wireless Communications and Networking Conference, WCNC 2008, Las Vegas, NV, United States, 3/31/08.
Howard SL, Flikkema PG. Integrated source-channel decoding for correlated data-gathering sensor networks. In IEEE Wireless Communications and Networking Conference, WCNC. 2008. p. 1261-1266. 4489258
Howard, Sheryl L ; Flikkema, Paul G. / Integrated source-channel decoding for correlated data-gathering sensor networks. IEEE Wireless Communications and Networking Conference, WCNC. 2008. pp. 1261-1266
@inproceedings{1811eede10aa460b879f4884c9a4d0e3,
title = "Integrated source-channel decoding for correlated data-gathering sensor networks",
abstract = "This paper explores integrated source-channel decoding, driven by wireless sensor network applications where correlated information acquired by the network is gathered at a destination node. The collection of coded measurements sent to the destination, called a source-channel product codeword, has redundancy due to both correlation of the measurements and the channel code used for each measurement. At the destination, source-channel (SC) decoding of this code combines decoding using (i) the deterministic structure of the channel-coded individual measurements and (ii) the probabilistic structure of a prior model, called the global model, that describes the correlation structure of the SC product codewords. We demonstrate the utility of SC decoding via MAP SC decoding experiments using a (7,4,3) Hamming code and a Gaussian global model. We also show that SC decoding can exploit even the simplest possible code, a single-parity check code, using a MAP SC decoder that integrates the parity check constraint and global model. We describe the design of a low-complexity message-passing decoder and show it can improve performance in the poor-quality channels often found in multi-hop wireless data-gathering sensor networks.",
author = "Howard, {Sheryl L} and Flikkema, {Paul G}",
year = "2008",
language = "English (US)",
isbn = "9781424419968",
pages = "1261--1266",
booktitle = "IEEE Wireless Communications and Networking Conference, WCNC",

}

TY - GEN

T1 - Integrated source-channel decoding for correlated data-gathering sensor networks

AU - Howard, Sheryl L

AU - Flikkema, Paul G

PY - 2008

Y1 - 2008

N2 - This paper explores integrated source-channel decoding, driven by wireless sensor network applications where correlated information acquired by the network is gathered at a destination node. The collection of coded measurements sent to the destination, called a source-channel product codeword, has redundancy due to both correlation of the measurements and the channel code used for each measurement. At the destination, source-channel (SC) decoding of this code combines decoding using (i) the deterministic structure of the channel-coded individual measurements and (ii) the probabilistic structure of a prior model, called the global model, that describes the correlation structure of the SC product codewords. We demonstrate the utility of SC decoding via MAP SC decoding experiments using a (7,4,3) Hamming code and a Gaussian global model. We also show that SC decoding can exploit even the simplest possible code, a single-parity check code, using a MAP SC decoder that integrates the parity check constraint and global model. We describe the design of a low-complexity message-passing decoder and show it can improve performance in the poor-quality channels often found in multi-hop wireless data-gathering sensor networks.

AB - This paper explores integrated source-channel decoding, driven by wireless sensor network applications where correlated information acquired by the network is gathered at a destination node. The collection of coded measurements sent to the destination, called a source-channel product codeword, has redundancy due to both correlation of the measurements and the channel code used for each measurement. At the destination, source-channel (SC) decoding of this code combines decoding using (i) the deterministic structure of the channel-coded individual measurements and (ii) the probabilistic structure of a prior model, called the global model, that describes the correlation structure of the SC product codewords. We demonstrate the utility of SC decoding via MAP SC decoding experiments using a (7,4,3) Hamming code and a Gaussian global model. We also show that SC decoding can exploit even the simplest possible code, a single-parity check code, using a MAP SC decoder that integrates the parity check constraint and global model. We describe the design of a low-complexity message-passing decoder and show it can improve performance in the poor-quality channels often found in multi-hop wireless data-gathering sensor networks.

UR - http://www.scopus.com/inward/record.url?scp=51649121263&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=51649121263&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:51649121263

SN - 9781424419968

SP - 1261

EP - 1266

BT - IEEE Wireless Communications and Networking Conference, WCNC

ER -