ECRB-Based Optimal Parameter Encoding Under Secrecy Constraints - 2018 PROJECT TITLE :ECRB-Based Optimal Parameter Encoding Under Secrecy Constraints - 2018ABSTRACT:In this Project, optimal deterministic encoding of a scalar parameter is investigated in the presence of an eavesdropper. The aim is to minimize the expectation of the conditional Cramér-Rao bound at the supposed receiver while keeping the mean-squared error (MSE) at the eavesdropper on top of a sure threshold. Initial, optimal encoding functions are derived within the absence of secrecy constraints for any given prior distribution on the parameter. Next, an optimization problem is formulated below a secrecy constraint and numerous answer approaches are proposed. Conjointly, theoretical results on the shape of the optimal encoding operate are provided beneath the idea that the eavesdropper employs a linear minimum mean-squared error (MMSE) estimator. Numerical examples are presented to illustrate the theoretical results and to investigate the performance of the proposed resolution approaches. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Double Coupled Canonical Polyadic Decomposition for Joint Blind Source Separation - 2018 Efficient Compressive Channel Estimation for Millimeter-Wave Large-Scale Antenna Systems - 2018
