TY - GEN
T1 - Dimensionality reduction with automatic dimension assignment for distributed estimation
AU - Fang, Jun
AU - Li, Hongbin
PY - 2008
Y1 - 2008
N2 - We consider distributed estimation of a random vector parameter by a wireless sensor network (WSN). To meet stringent power and bandwidth budgets in WSN, local data compression is performed at each sensor to reduce the number of messages sent to a fusion center (FC). Under the constraint of a given total number of messages, our problem is to jointly determine the number of messages sent by each senor (a.k.a. dimension assignment) and design the corresponding compression matrix. The problem is formulated as a constrained optimization problem that minimizes the estimation mean-square error (MSE) at the FC. We analyze the problem using a subspace projection technique, which yields an efficient iterative solution. Numerical results are presented to illustrate the effectiveness of the proposed algorithm.
AB - We consider distributed estimation of a random vector parameter by a wireless sensor network (WSN). To meet stringent power and bandwidth budgets in WSN, local data compression is performed at each sensor to reduce the number of messages sent to a fusion center (FC). Under the constraint of a given total number of messages, our problem is to jointly determine the number of messages sent by each senor (a.k.a. dimension assignment) and design the corresponding compression matrix. The problem is formulated as a constrained optimization problem that minimizes the estimation mean-square error (MSE) at the FC. We analyze the problem using a subspace projection technique, which yields an efficient iterative solution. Numerical results are presented to illustrate the effectiveness of the proposed algorithm.
KW - Distributed estimation
KW - Joint dimension assignment and compression
KW - Wireless sensor network (WSN)
UR - http://www.scopus.com/inward/record.url?scp=51449089850&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=51449089850&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2008.4518213
DO - 10.1109/ICASSP.2008.4518213
M3 - Conference contribution
AN - SCOPUS:51449089850
SN - 1424414849
SN - 9781424414840
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 2729
EP - 2732
BT - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
T2 - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Y2 - 31 March 2008 through 4 April 2008
ER -