Master of Science / Department of Electrical and Computer Engineering / Balasubramaniam Natarajan / In this thesis, we first consider the problem of distributed estimation in an
energy and rate-constrained wireless sensor network. To this end, we study three
estimators namely - (1) Best Linear Unbiased Estimator (BLUE-1) that accounts for
the variance of noise in measurement, uniform quantization and channel, and derive
its variance and its lower bound; (2) Best Linear Unbiased Estimator (BLUE-2) that
accounts for the variance of noise in measurement and uniform quantization, and
derive lower and upper bounds for its variance; (3) Best Linear Unbiased Estima-
tor (BLUE-3) that incorporates the effects of probabilistic quantization noise and
measurement noise, and derive an upper bound for its variance.
Then using BLUE-1, we analyze the tradeoff between estimation error (BLUE
variance) at the fusion center and the total amount of resources utilized (power and
rate) using three different system design approaches or optimization formulations.
For all the formulations, we determine optimum quantization bits and transmission
power per bit (or optimum actions) for all sensors jointly. Unlike prior efforts, we in-
corporate the operating state (characterized by the amount of residual battery power)
of the sensors in the optimization framework. We study the e®ect of channel quality, local measurement noise, and operating states of the sensors on their optimum choice for quantization bits and transmit power per bit.
In the sequel, we consider a problem in distributed detection and signal
processing in the context of biomedical wireless sensors and more specifically pulse-
oximeter devices that record photoplethysmographic data. We propose an automated, two-stage PPG data processing method to minimize the effect of motion artifact.
Regarding stage one, we present novel and consistent techniques to detect the presence
of motion artifact in photoplethysmograms given higher order statistical information
present in the data.For stage two, we propose an effective motion artifact reduction
method that involves enhanced PPG data preprocessing followed by frequency domain
Independent Component Analysis (FD-ICA). Experimental results are presented to
demonstrate the efficacy of the overall motion artifact reduction method.
Finally, we analyze a wireless ad hoc/sensor network where nodes are connected via random channels and information is transported in the network in a cooperative multihop fashion using amplify and forward relay strategy.
| Identifer | oai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/1351 |
| Date | January 1900 |
| Creators | Krishnan, Rajet |
| Publisher | Kansas State University |
| Source Sets | K-State Research Exchange |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
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