mca 16(7): e5

Research Article

Evaluation of different signal propagation models for a mixed indoor-outdoor scenario using empirical data

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  • @ARTICLE{10.4108/eai.20-6-2016.151519,
        author={Oleksandr Artemenko and Alina Rubina and Adarsh Harishchandra Nayak and Sanjeeth Baptist Menezes and Andreas Mitschele-Thiel},
        title={Evaluation of different signal propagation models for a mixed indoor-outdoor scenario using empirical data},
        journal={EAI Endorsed Transactions on Mobile Communications and Applications},
        volume={2},
        number={7},
        publisher={EAI},
        journal_a={MCA},
        year={2016},
        month={6},
        keywords={Path loss, Signal propagation models, Signal strength, Experiment},
        doi={10.4108/eai.20-6-2016.151519}
    }
    
  • Oleksandr Artemenko
    Alina Rubina
    Adarsh Harishchandra Nayak
    Sanjeeth Baptist Menezes
    Andreas Mitschele-Thiel
    Year: 2016
    Evaluation of different signal propagation models for a mixed indoor-outdoor scenario using empirical data
    MCA
    EAI
    DOI: 10.4108/eai.20-6-2016.151519
Oleksandr Artemenko1, Alina Rubina1,*, Adarsh Harishchandra Nayak1, Sanjeeth Baptist Menezes1, Andreas Mitschele-Thiel1
  • 1: Integrated Communication Systems Group, The Department of Computer Science & Automation, Technische Universit√§t Ilmenau, 98693 Ilmenau, Germany
*Contact email: alina.rubina@tu-ilmenau.de

Abstract

In this paper, we are choosing a suitable indoor-outdoor propagation model out of the existing models by considering path loss and distance as parameters. A path loss is calculated empirically by placing emitter nodes inside a building. A receiver placed outdoors is represented by a Quadrocopter (QC) that receives beacon messages from indoor nodes. As per our analysis, the International Telecommunication Union (ITU) model, Stanford University Interim (SUI) model, COST-231 Hata model, Green-Obaidat model, Free Space model, Log-Distance Path Loss model and Electronic Communication Committee 33 (ECC-33) models are chosen and evaluated using empirical data collected in a real environment. The aim is to determine if the analytically chosen models fit our scenario by estimating the minimal standard deviation from the empirical data.