TY - GEN
T1 - Adaptive quantization and distributed estimation for bandwidth-constraint sensor networks
AU - Li, Hongbin
AU - Fang, Jun
PY - 2007
Y1 - 2007
N2 - In this paper, the problem of distributed parameter estimation in a wireless sensor network is considered, where due to bandwidth constraint, each sensor node sends only one bit of information per sample to a fusion center. We propose a new distributed adaptive quantization scheme by which each individual sensor node dynamically adjusts the threshold of its quantizer based on earlier transmissions from other sensor nodes. The maximum likelihood estimator (MLE) and the Cramér-Rao bound (CRB) associated with our distributed adaptive quantization scheme are derived. Numerical results depicting the performance and advantages of our approach over a fixed quantization scheme are presented.
AB - In this paper, the problem of distributed parameter estimation in a wireless sensor network is considered, where due to bandwidth constraint, each sensor node sends only one bit of information per sample to a fusion center. We propose a new distributed adaptive quantization scheme by which each individual sensor node dynamically adjusts the threshold of its quantizer based on earlier transmissions from other sensor nodes. The maximum likelihood estimator (MLE) and the Cramér-Rao bound (CRB) associated with our distributed adaptive quantization scheme are derived. Numerical results depicting the performance and advantages of our approach over a fixed quantization scheme are presented.
KW - Adaptive quantization
KW - Distributed estimation
KW - Wireless sensor networks
UR - http://www.scopus.com/inward/record.url?scp=51649085590&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=51649085590&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2007.4557295
DO - 10.1109/ISIT.2007.4557295
M3 - Conference contribution
AN - SCOPUS:51649085590
SN - 1424414296
SN - 9781424414291
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 631
EP - 635
BT - Proceedings - 2007 IEEE International Symposium on Information Theory, ISIT 2007
T2 - 2007 IEEE International Symposium on Information Theory, ISIT 2007
Y2 - 24 June 2007 through 29 June 2007
ER -