TY - GEN
T1 - A study of hyperplane-based vector quantization for distributed estimation
AU - Fang, Jun
AU - Li, Hongbin
PY - 2010
Y1 - 2010
N2 - We consider the problem of distributed estimation of a vector parameter in wireless sensor networks (WSNs). Due to stringent power and bandwidth constraints, vector quantization is performed at each sensor to convert its local noisy vector observation into one bit of information. The one bit quantized data is then sent to the fusion center (FC), where a final estimate of the vector parameter is formed. The vector quantization problem is studied in such a distributed estimation context. Specifically, our study focuses on a class of hyperplane-based vector quantizers which linearly convert the observation vector into a scalar by using a compression vector and then carry out a scalar quantization. Under the framework of the Cramér-Rao bound (CRB) analysis, we study the choice of the quantization thresholds and the design of the compression vectors.
AB - We consider the problem of distributed estimation of a vector parameter in wireless sensor networks (WSNs). Due to stringent power and bandwidth constraints, vector quantization is performed at each sensor to convert its local noisy vector observation into one bit of information. The one bit quantized data is then sent to the fusion center (FC), where a final estimate of the vector parameter is formed. The vector quantization problem is studied in such a distributed estimation context. Specifically, our study focuses on a class of hyperplane-based vector quantizers which linearly convert the observation vector into a scalar by using a compression vector and then carry out a scalar quantization. Under the framework of the Cramér-Rao bound (CRB) analysis, we study the choice of the quantization thresholds and the design of the compression vectors.
KW - Distributed estimation
KW - Hyperplane-based vector quantization
KW - Wireless sensor network (WSN)
UR - http://www.scopus.com/inward/record.url?scp=78049377595&partnerID=8YFLogxK
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U2 - 10.1109/ICASSP.2010.5496171
DO - 10.1109/ICASSP.2010.5496171
M3 - Conference contribution
AN - SCOPUS:78049377595
SN - 9781424442966
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 2898
EP - 2901
BT - 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
T2 - 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
Y2 - 14 March 2010 through 19 March 2010
ER -