Problems in distributed signal processing in wireless sensor networks.
Rajet Krishnan · K-State Research Exchange (Kansas State University) · 2009
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 Estimator (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