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2019-07-17

Bayesian Approach for Indoor Wave Propagation Modeling

By Abdullah Al-Ahmadi, Yazeed Mohammad Qasaymeh, Praveen R. P., and Ali Alghamdi
Progress In Electromagnetics Research M, Vol. 83, 41-50, 2019
doi:10.2528/PIERM19042804

Abstract

This paper presents a parsimonious Bayesian indoor wave propagation model for predicting signal power in multi-wall multi-floor complex indoor environments. The received power is modeled as a Bayesian multiple regression model. The parameters of the model are assessed and validated using a two-tier validation strategy in which Bayes factor and posterior probability are used in the first tier and second tier, respectively. The performance of the two-tier strategy is then assessed using Bayesian information criterion. The proposed indoor propagation model is tested in a two-storey building with access points operating at 2.4 GHz.

Citation


Abdullah Al-Ahmadi, Yazeed Mohammad Qasaymeh, Praveen R. P., and Ali Alghamdi, "Bayesian Approach for Indoor Wave Propagation Modeling," Progress In Electromagnetics Research M, Vol. 83, 41-50, 2019.
doi:10.2528/PIERM19042804
http://jpier.org/PIERM/pier.php?paper=19042804

References


    1. Madigan, D., E. Elnahrawy, R. P. Martin, W. H. Ju, P. Krishnan, and A. S. Krishnakumar, "Bayesian indoor positioning systems," Proceedings - IEEE INFOCOM, Vol. 2, 1217-1227, 2005.

    2. Al-Ahmadi, A., A. I. A. Omer, M. R. Kamarudin, and T. A. Rahman, "Multi-floor indoor positioning system using Bayesian graphical models," Progress In Electromagnetics Research B, Vol. 25, 241-259, 2010.
    doi:10.2528/PIERB10081202

    3. Xu, H., Y. Ding, P. Li, R. Wang, and Y. Li, "An RFID indoor positioning algorithm based on Bayesian probability and K-Nearest Neighbor," Sensors, Vol. 17, No. 8, 1806, Switzerland, Aug. 2017.
    doi:10.3390/s17081806

    4. Zaman, T., E. B. Fox, and E. T. Bradlow, "A Bayesian approach for predicting the popularity of tweets," Annals of Applied Statistics, Vol. 8, No. 3, 1583-1611, 2014.
    doi:10.1214/14-AOAS741

    5. Steorts, R. C., R. Hall, and S. E. Fienberg, "A Bayesian approach to graphical record linkage and deduplication," Journal of the American Statistical Association, Vol. 111, No. 516, 1660-1672, 2016.
    doi:10.1080/01621459.2015.1105807

    6. Campisi, P. and K. Egiazarian, Blind Image Deconvolution: Theory and Applications, 1st Ed., CRC Press, 2007.

    7. Kruschke, J. K. and T. M. Liddell, "Bayesian data analysis for newcomers," Psychonomic Bulletin and Review, Vol. 25, No. 1, 155-177, 2018.
    doi:10.3758/s13423-017-1272-1

    8. Damosso, E., "Digital mobile radio towards future generation systems: COST action 231,", European Commission, 1999.

    9. Tarng, J. H. and T. R. Liu, "Effective models in evaluating radio coverage on single floors of multifloor buildings," IEEE Transactions on Vehicular Technology, Vol. 48, No. 3, 782-789, 1999.
    doi:10.1109/25.764994

    10. Lawton, M. C. and J. P. McGeehan, "The application of a deterministic ray launching algorithm for the prediction of radio channel characteristics in small-cell environments," IEEE Transactions on Vehicular Technology, Vol. 43, No. 4, 955-969, Nov. 1994.
    doi:10.1109/25.330158

    11. Herring, K. T., J. W. Holloway, D. H. Staelin, and D. W. Bliss, "Path-loss characteristics of urban wireless channels," IEEE Transactions on Antennas and Propagation, Vol. 58, No. 1, 171-177, Jan. 2010.
    doi:10.1109/TAP.2009.2036278

    12. Malnar, M. and N. Jevtic, "Novel multi-room multi-obstacle indoor propagation model for wireless networks," Wireless Personal Communications, Vol. 102, No. 1, 583-597, Sep. 2018.
    doi:10.1007/s11277-018-5859-2

    13. Rouder, J. N. and R. D. Morey, "Default Bayes factors for model selection in regression," Multivariate Behavioral Research, Vol. 47, No. 6, 877-903, Nov. 2012.
    doi:10.1080/00273171.2012.734737

    14. Posada, D. and T. R. Buckley, "Model selection and model averaging in phylogenetics: Advantages of akaike information criterion and Bayesian approaches over likelihood ratio tests," Syst. Biol., Vol. 53, No. 5, 793-808, Oct. 2004.
    doi:10.1080/10635150490522304

    15. Clyde, M., "BAS: Bayesian variable selection and model averaging using Bayesian adaptive sampling,", R package version 1.5.3, 2018.

    16. Al-Ahmadi, A. S., T. A. Rahman, M. R. Kamarudin, M. H. Jamaluddin, and A. I. Omer, "Single-phase wireless LAN based multi-floor indoor location determination system," 2011 IEEE 17th International Conference on Parallel and Distributed Systems, 1057-1062, IEEE, Dec. 2011.
    doi:10.1109/ICPADS.2011.122

    17. Al-Ahmadi, A. and T. A. Rahman, "One stage indoor location determination systems," New Approach of Indoor and Outdoor Localization Systems, F. B. Elbahhar and A. Rivenq, editors, Chapter 8, IntechOpen, Rijeka, 2012.