Blind Source Separation for Complex-Valued Signals Using Generalized Autocorrelation

Xiaogang Tang, Sun’an Wang and Jiong Li

Mathematical Problems in Engineering, 2018, vol. 2018, 1-9

Abstract:

We introduce a new complex-valued blind source separation approach, based on generalized autocorrelations of sources, to improve the spectrum efficiency for the next-generation wireless communications system. The proposed algorithm considers the temporal structures of communication signals and the natural gradient-based method is used to optimize the demixing matrix. In addition, the local stability condition is proved. Simulation results are presented showing the superior performance of the proposed algorithm in the intersymbol interference of the estimated signals.

Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2018/8076468.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2018/8076468.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:8076468

DOI: 10.1155/2018/8076468

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().