1st International Conference on 5G for Ubiquitous Connectivity

Research Article

Interference Empowered 5G Networks

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  • @INPROCEEDINGS{10.4108/icst.5gu.2014.258227,
        author={Matthieu DE MARI and Emilio CALVANESE STRINATI and Merouane DEBBAH and Zdenek Becvar},
        title={Interference Empowered 5G Networks},
        proceedings={1st International Conference on 5G for Ubiquitous Connectivity},
        publisher={IEEE},
        proceedings_a={5GU},
        year={2014},
        month={12},
        keywords={spectral efficiency matching interference classification 5g networks},
        doi={10.4108/icst.5gu.2014.258227}
    }
    
  • Matthieu DE MARI
    Emilio CALVANESE STRINATI
    Merouane DEBBAH
    Zdenek Becvar
    Year: 2014
    Interference Empowered 5G Networks
    5GU
    IEEE
    DOI: 10.4108/icst.5gu.2014.258227
Matthieu DE MARI, Emilio CALVANESE STRINATI1,*, Merouane DEBBAH2, Zdenek Becvar3
  • 1: CEA
  • 2: Supélec
  • 3: Czech Technical University in Prague
*Contact email: emilio.calvanese-strinati@cea.fr

Abstract

In future 5G networks, in-band interference is perceived as one of the most critical performance bottlenecks. While current solutions classically treat interference as an additional source of noise, recent advances in information theory show that interference is not necessarily an opponent, but might be cancelled or supressed. In this paper, we propose a threefold optimization method, which couples reduced complexity interference classification and matching techniques, to enhance the system performance. The matching objective consists in i) defining coalitions of users assigned to each Access Points (AP); ii) match interferers that will be transmitting on the same spectral resources into groups of interferers; and iii) define the transmission rates and interference regimes for each user inside each group. Our analytical study and simulations results show that our proposed solution allows for system spectral efficiency enhancements, compared to classical reference scenarios.