TY - GEN
T1 - Distributed estimation in sensor networks over binary symmetric channels
AU - Kumar, Kiran Sampath
AU - Li, Hongbin
PY - 2009
Y1 - 2009
N2 - We consider distributed parameter estimation using quantized observations in wireless sensor networks (WSN) over binary symmetric channels. Due to stringent bandwidth and power constraints, each sensor quantizes its local observation into one bit of information. Previously, adaptive quantization(AQ) schemes were developed under the assumption of perfect communication links in the WSN. In this paper we propose an adaptive quantization scheme for a WSN with channel links modeled as binary symmetric channels. A Hidden Markov Model (HMM) framework is introduced to model the adaptive quantization scheme.We propose an expectation maximization based estimator at the fusion center to form an estimate from the quantized bits. Approximate closed form solutions for the Cramer-Rao lower bounds are developed for the proposed estimation problem. We analyze the performance of the proposed quantization scheme and estimator under different criteria. Numerical simulation results are shown for the proposed adaptive quantization and estimation scheme under different scenarios. The simulation results indicate that the proposed quantization scheme and estimator are robust and can provide superior performance for crossover rates up to 10 %.
AB - We consider distributed parameter estimation using quantized observations in wireless sensor networks (WSN) over binary symmetric channels. Due to stringent bandwidth and power constraints, each sensor quantizes its local observation into one bit of information. Previously, adaptive quantization(AQ) schemes were developed under the assumption of perfect communication links in the WSN. In this paper we propose an adaptive quantization scheme for a WSN with channel links modeled as binary symmetric channels. A Hidden Markov Model (HMM) framework is introduced to model the adaptive quantization scheme.We propose an expectation maximization based estimator at the fusion center to form an estimate from the quantized bits. Approximate closed form solutions for the Cramer-Rao lower bounds are developed for the proposed estimation problem. We analyze the performance of the proposed quantization scheme and estimator under different criteria. Numerical simulation results are shown for the proposed adaptive quantization and estimation scheme under different scenarios. The simulation results indicate that the proposed quantization scheme and estimator are robust and can provide superior performance for crossover rates up to 10 %.
UR - http://www.scopus.com/inward/record.url?scp=77953854841&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77953854841&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2009.5470106
DO - 10.1109/ACSSC.2009.5470106
M3 - Conference contribution
AN - SCOPUS:77953854841
SN - 9781424458271
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 265
EP - 269
BT - Conference Record - 43rd Asilomar Conference on Signals, Systems and Computers
T2 - 43rd Asilomar Conference on Signals, Systems and Computers
Y2 - 1 November 2009 through 4 November 2009
ER -