TY - GEN
T1 - An energy efficient iterative method for source localization in wireless sensor networks
AU - Masazade, Engin
AU - Niu, Ruixin
AU - Varshney, Pramod K.
AU - Keskinoz, Mehmet
PY - 2009
Y1 - 2009
N2 - In this paper, we study the source localization problem in wireless sensor networks. Sensors transmit their quantized signal amplitude measurements to the fusion center and source location is estimated based on these quantized measurements. In this paper, we propose an energy efficient iterative localization scheme, where the algorithm starts with a coarse location estimate obtained from a set of anchor sensors. At each consecutive iteration, some of the non anchor sensors are activated which minimize the Posterior Cramer Rao Lower Bound (PCRLB). Then, using the available information received at previous iterations as side information, the quantized data of each activated sensor is further compressed to conserve energy using distributed data compression techniques prior to transmission to the fusion center. Simulation results show that the proposed iterative method achieves the same estimation performance as when all the sensors transmit their quantized data to the fusion center within a few iterations, while at the same time significantly reducing the communication requirements resulting in energy savings.
AB - In this paper, we study the source localization problem in wireless sensor networks. Sensors transmit their quantized signal amplitude measurements to the fusion center and source location is estimated based on these quantized measurements. In this paper, we propose an energy efficient iterative localization scheme, where the algorithm starts with a coarse location estimate obtained from a set of anchor sensors. At each consecutive iteration, some of the non anchor sensors are activated which minimize the Posterior Cramer Rao Lower Bound (PCRLB). Then, using the available information received at previous iterations as side information, the quantized data of each activated sensor is further compressed to conserve energy using distributed data compression techniques prior to transmission to the fusion center. Simulation results show that the proposed iterative method achieves the same estimation performance as when all the sensors transmit their quantized data to the fusion center within a few iterations, while at the same time significantly reducing the communication requirements resulting in energy savings.
UR - http://www.scopus.com/inward/record.url?scp=70349678821&partnerID=8YFLogxK
U2 - 10.1109/CISS.2009.5054794
DO - 10.1109/CISS.2009.5054794
M3 - Conference contribution
AN - SCOPUS:70349678821
SN - 9781424427345
T3 - Proceedings - 43rd Annual Conference on Information Sciences and Systems, CISS 2009
SP - 623
EP - 628
BT - Proceedings - 43rd Annual Conference on Information Sciences and Systems, CISS 2009
T2 - 43rd Annual Conference on Information Sciences and Systems, CISS 2009
Y2 - 18 March 2009 through 20 March 2009
ER -