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Extension of the Sequentially Drilled Joint Congruence transformation (SeDJoCo) problem

Yao Cheng, Arie Yeredor, Amir Weiss, Martin Haardt

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The Sequentially Drilled Joint Congruence (SeDJoCo) transformation has been identified as an important tool in the context of both Blind Source Separation (BSS) and closed-form Coordinated Beamforming (CBF) for the multi-user MIMO downlink. It can be interpreted as a new tensor decomposition. In this contribution, we introduce an extension of the SeDJoCo problem and address its links to the field of Independent Vector Analysis (IVA) and to CBF in a multicast framework. A solution of the extended SeDJoCo problem is proposed by extending the LU decomposition-based concept that is frequently used for joint matrix diagonalization. Data sets in an IVA setup are used in numerical simulations which show that the proposed algorithm is very efficient in finding the exact solution for the extended SeDJoCo problem, at least in a two-data-set case.

Original languageEnglish
Title of host publication2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages185-188
Number of pages4
ISBN (Electronic)9781479919635
DOIs
StatePublished - 2015
Event6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015 - Cancun, Mexico
Duration: 13 Dec 201516 Dec 2015

Publication series

Name2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015

Conference

Conference6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
Country/TerritoryMexico
CityCancun
Period13/12/1516/12/15

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computational Mathematics

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