Publications in Scientific Journals:
S. Schwarz, T. Tsiftsis:
"Codebook Training for Trellis-Based Hierarchical Grassmannian Classification";
IEEE Wireless Communications Letters,
11
(2022),
3;
636
- 640.
English abstract:
We consider classification of points on a complex-valued Grassmann manifold of m-dimensional subspaces within the n-dimensional complex Euclidean space. We introduce a trellis-based hierarchical classification network, which is based on an orthogonal product decomposition of the orthogonal basis representing the m-dimensional subspace. Exploiting the similarity of the proposed trellis classifier with a neural network, we propose stochastic gradient-based training techniques. We apply the proposed methods to two important applications in wireless communication, namely Grassmannian channel state information quantization in multiple-input multiple-output communications and non-coherent Grassmannian multi-resolution transmission.
Keywords:
Grassmannian classification, CSI quantization, non-coherent transmission, trellis network training
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.1109/LWC.2021.3139166
Electronic version of the publication:
https://publik.tuwien.ac.at/files/publik_301185.pdf
Created from the Publication Database of the Vienna University of Technology.