Robust interference identification for multi-RAT optimization in wireless cellular networks

Author

Pollakis, E. ; Cavalcante, R.L.G. ; Stanczak, Slawomir ; Penna, Federico

Author_Institution

Fraunhofer Inst. for Telecommun., Heinrich Hertz Inst., Berlin, Germany

fYear

2012

fDate

16-19 Oct. 2012

Firstpage

284

Lastpage

284

Abstract

The objective of this study is to devise novel cognitive interference identification techniques for UMTS and LTE networks. We apply machine learning techniques to reconstruct interference patterns using a priori system knowledge, limited user information and sparse pathloss and interference measurements. The obtained interference patterns are used to build a multi-RAT optimization procedure aiming at energy efficient operation.

Keywords

3G mobile communication; Long Term Evolution; cellular radio; learning (artificial intelligence); optimisation; radiofrequency interference; radiofrequency measurement; telecommunication computing; LTE networks; UMTS; cognitive interference identification techniques; interference measurements; interference patterns reconstruction; machine learning techniques; multiRAT optimization; robust interference identification; sparse pathloss; user information; wireless cellular networks; 3G mobile communication; Energy consumption; Interference; Optimization; Quality of service; Signal processing algorithms; Wireless communication;

fLanguage

English

Publisher

ieee

Conference_Titel

Dynamic Spectrum Access Networks (DYSPAN), 2012 IEEE International Symposium on

Conference_Location

Bellevue, WA

Print_ISBN

978-1-4673-4447-0

Electronic_ISBN

978-1-4673-4446-3

Type

conf

DOI

10.1109/DYSPAN.2012.6478147

Filename

6478147