TY - GEN
T1 - On optimal sensor collaboration topologies for linear coherent estimation
AU - Liu, Sijia
AU - Fardad, Makan
AU - Kar, Swarnendu
AU - Varshney, Pramod K.
PY - 2014
Y1 - 2014
N2 - In the context of distributed estimation we consider the problem of sensor collaboration, which refers to the act of sharing measurements with neighboring sensors prior to transmission to a fusion center. While incorporating the cost of sensor collaboration, we aim to find optimal sparse collaboration topologies subject to a certain information or energy constraint. To achieve this goal, we present a tractable optimization framework and propose efficient methods to solve the formulated sensor collaboration problems. The effectiveness of our approach is demonstrated by numerical examples.
AB - In the context of distributed estimation we consider the problem of sensor collaboration, which refers to the act of sharing measurements with neighboring sensors prior to transmission to a fusion center. While incorporating the cost of sensor collaboration, we aim to find optimal sparse collaboration topologies subject to a certain information or energy constraint. To achieve this goal, we present a tractable optimization framework and propose efficient methods to solve the formulated sensor collaboration problems. The effectiveness of our approach is demonstrated by numerical examples.
UR - http://www.scopus.com/inward/record.url?scp=84906536030&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84906536030&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2014.6875309
DO - 10.1109/ISIT.2014.6875309
M3 - Conference contribution
AN - SCOPUS:84906536030
SN - 9781479951864
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 2624
EP - 2628
BT - 2014 IEEE International Symposium on Information Theory, ISIT 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Symposium on Information Theory, ISIT 2014
Y2 - 29 June 2014 through 4 July 2014
ER -