Minimum Energy Decentralized Estimation in a Wireless Sensor Network with Correlated Sensor Noises

• Main Authors: Krasnopeev Alexey, Xiao Jin-Jun, Luo Zhi-Quan
• Format: Article
• Language: English
• Published: SpringerOpen 2005-01-01
• Series: EURASIP Journal on Wireless Communications and Networking
• Subjects: wireless sensor networks; decentralized estimation; power control; energy efficiency
• Online Access: http://jwcn.eurasipjournals.com/content/2005/919686

<p/> <p>Consider the problem of estimating an unknown parameter by a sensor network with a fusion center (FC). Sensor observations are corrupted by additive noises with an arbitrary spatial correlation. Due to bandwidth and energy limitation, each sensor is only able to transmit a finite number of bits to the FC, while the latter must combine the received bits to estimate the unknown parameter. We require the decentralized estimator to have a mean-squared error ( <inline-formula><graphic file="1687-1499-2005-919686-i1.gif"/></inline-formula>) that is within a constant factor to that of the best linear unbiased estimator (BLUE). We minimize the total sensor transmitted energy by selecting sensor quantization levels using the knowledge of noise covariance matrix while meeting the target <inline-formula><graphic file="1687-1499-2005-919686-i2.gif"/></inline-formula> requirement. Computer simulations show that our designs can achieve energy savings up to <inline-formula><graphic file="1687-1499-2005-919686-i3.gif"/></inline-formula> when compared to the uniform quantization strategy whereby each sensor generates the same number of bits, irrespective of the quality of its observation and the condition of its channel to the FC.</p>