| Full text | |
| Author(s): |
Total Authors: 3
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| Affiliation: | [1] Univ Estadual Campinas, DSPCom Lab, Campinas, SP - Brazil
[2] Univ Nice Sophia Antipolis, CNRS, Lab I3S, Sophia Antipolis - France
Total Affiliations: 2
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| Document type: | Journal article |
| Source: | Signal Processing; v. 145, p. 304-316, APR 2018. |
| Web of Science Citations: | 8 |
| Abstract | |
The purpose of this paper is manifold. In a first part, we present a new alternating least squares (ALS)-based method for estimating the matrix factors of a Kronecker product, the so-called Kronecker ALS. (KALS) method. Four other methods are also briefly described. In a second part, we consider the design of multiple-input multiple-output (MIMO) wireless communication systems using tensor modelling. Eight systems are presented in a unified way, and their theoretical performance is compared in terms of maximal diversity gain. Exploiting a Kronecker product of symbol and channel matrices, and applying the algorithms introduced in the first part, we propose three semi-blind and two supervised receivers, called Kronecker receivers, for jointly estimating the channel and the transmitted symbols. Necessary identifiability conditions are established. Finally, extensive Monte Carlo simulation results are provided to compare the performance of three tensor-based systems, on the one hand, and of the five proposed Kronecker receivers for the tensor space-time-frequency (TSTF) coding system, on the other hand. (C) 2017 Elsevier B.V. All rights reserved. (AU) | |
| FAPESP's process: | 14/23936-4 - Applications of multidimensional data processing using tensor methods |
| Grantee: | Michele Nazareth da Costa |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |