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
Recommended Citation
Fahad, M.,
&
Fuhrmann, D.
(2022).
Sensing Method for Two-Target Detection in Time-Constrained Vector Gaussian Channel.
International Journal of Information Theory,
11(1).
http://doi.org/10.5121/ijit.2022.11101
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/15923