Innovation and Interdisciplinary Solutions for Underserved Areas. First International Conference, InterSol 2017 and Sixth Collogue National sur la Recherche en Informatique et ses Applications, CNRIA 2017, Dakar, Senegal, April 11–12, 2017, Proceedings

Research Article

Geometric Approach of Blind Channel Estimation

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  • @INPROCEEDINGS{10.1007/978-3-319-72965-7_22,
        author={Agbeti Ahossi and Ahmed Kora and Roger Faye},
        title={Geometric Approach of Blind Channel Estimation},
        proceedings={Innovation and Interdisciplinary Solutions for Underserved Areas. First International Conference, InterSol 2017 and Sixth Collogue National sur la Recherche en Informatique et ses Applications, CNRIA 2017, Dakar, Senegal, April 11--12, 2017, Proceedings},
        proceedings_a={INTERSOL \& CNRIA},
        year={2018},
        month={2},
        keywords={Channel estimation Blind Geometric approach
     Sources separation MIMO},
        doi={10.1007/978-3-319-72965-7_22}
    }
    
  • Agbeti Ahossi
    Ahmed Kora
    Roger Faye
    Year: 2018
    Geometric Approach of Blind Channel Estimation
    INTERSOL & CNRIA
    Springer
    DOI: 10.1007/978-3-319-72965-7_22
Agbeti Ahossi1, Ahmed Kora2,*, Roger Faye1
  • 1: Ecole Supérieure Polytechnique, Université Cheikh Anta Diop
  • 2: Ecole Supérieure Multinationale des Télécommunications
*Contact email: ahmed.kora@esmt.sn

Abstract

This paper introduces a geometric approach of channel estimation (GACE). It is a blind channel estimation method for multiple input multiple output systems. GACE is based on a two-step geometric approach of source separation (GASS) that outperforms the existing ones. It is an approximated maximum likelihood estimation method which proceeds by the determination of the polyhedral edges tilts representing the matrix parameters. It operates by identifying matrix parameters using a geometric consideration depending on the probabilistic hypothesis of the sources. The simplicity of this method is based on a cloud observation, which is used to determine the edge of parallelogram describing the matrix channel parameters. In this paper, the case of real channel parameters and complex data sources for higher modulation order are performed. The simulation results show the efficiency of the proposed approach.