Title

Sensing Method for Two-Target Detection in Time-Constrained Vector Gaussian Channel

Document Type

Article

Publication Date

1-2022

Department

Department of Applied Computing

Abstract

This paper considers a vector Gaussian channel of fixed identity covariance matrix and binary input signaling as the mean of it. A linear transformation is performed on the vector input signal. The objective is to find the optimal scaling matrix, under the total time constraint, that would: i) maximize the mutual information between the input and output random vectors, ii) maximize the MAP detection. It was found that the two metrics lead to different optimal solutions for our experimental design problem. We have used the Monte Carlo method for our computational work.

Publication Title

International Journal of Information Theory

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