Studi Komparatif Empat Model Propagasi Empiris Dalam Ruangan untuk Jaringan Wireless Kampus

Comparative Study of Four Indoor Empirical Propagation Models for Campus Wireless Network

*Fransiska Sisilia Mukti -  Department of Informatics, STMIK Asia Malang, Indonesia
Received: 6 May 2019; Revised: 11 Sep 2019; Accepted: 18 Sep 2019; Published: 31 Oct 2019; Available online: 3 Oct 2019.
Open Access Copyright (c) 2019 Jurnal Teknologi dan Sistem Komputer
Citation Format:
Article Info
Section: Articles
Language: ID
Statistics: 29

Abstract
Propagation is one of the important factors to understand in wireless communication systems. Prediction of the value of propagation, especially for closed areas, is very necessary to determine success in-building wireless networks. Various kinds of propagation modeling were developed to find the best approach to calculate the value of signal losses. A comparative study of 4 types of empirical propagation modeling was made to provide the most suitable propagation modeling analysis for campus wireless networks. The four propagation models tested in this study include One Slope Model, Log-distance Model, COST-231 Multiwall Model, and ITU-R (P.1238) Model). The test showed that the ITU-R model (P.1238) provides predictive results that are closest to the actual data in the field, with a relative error rate of 16.381%.
Keywords
propagation; wireless network; indoor; campus network

Article Metrics:

  1. M. Morocho-yaguana, P. Lude, F. Sandoval, B. Poma-v, and A. Erreyes-dota, “An Optimized Propagation Model based on Measurement Data for Indoor Environments,” J. Telecommun. Inf. Technol., vol. 2, pp. 69–75, 2018.
  2. J. C. Stein, “Indoor Radio WLAN Performance Part II : Range Performance in a Dense Office Environment,” Electron. Eng., pp. 1–9, 1998.
  3. L. Meiling, “Indoor Radio Propagation Modeling for System Performance Prediction,” INSA de Lyon, 2013.
  4. F. Agren, “Indoor Radio Propagation Modelling with Antenna Placement Optimization,” Lund University, 2017.
  5. P. Thu, Z. Tun, and A. S. Hlaing, “Modification of Propagation Prediction Model for 2.4 GHz Indoor Wireless Environment,” in International Conference on Advances in Engineering and Technology (ICAET), 2014, pp. 360–364.
  6. S. Y. Yeong, W. Al-Salihy, and T. C. Wan, “Indoor WLAN Monitoring and Planning using Empirical and Theoretical Propagation Models,” in Proceedings - 2nd International Conference on Network Applications, Protocols and Services, NETAPPS 2010, 2010, pp. 165–169.
  7. M. O. Omae, E. N. Ndungu, P. L. Kibet, and H. Tarus, “Artificial Intelligence Approach to Signal Propagation Modeling For Outdoor to Indoor Wireless Communication Networks ; A Proposed Study,” in Mechanical Engineering Conference on Sustainable Research and Innovation, 2012, vol. 4, no. May, pp. 289–299.
  8. F. J. Carlos Vesga, H. Martha Fabiola Contreras, and B. Jose Antonio Vesga, “Design of Empirical Propagation Models Supported in the Log-Normal Shadowing Model for the 2.4GHz and 5GHz Bands under Indoor Environments,” Indian J. Sci. Technol., vol. 11, no. 22, pp. 1–18, 2018.
  9. S. Zvanovec, P. Pechac, and M. Klepal, “Wireless LAN networks design: Site Survey or Propagation Modeling?,” Radioengineering, vol. 12, no. 4, pp. 42–49, 2003.
  10. F. S. Mukti and D. A. Sulistyo, “Analisis Penempatan Access Point Pada Jaringan Wireless LAN STMIK Asia Malang Menggunakan One Slope Model,” J. Ilm. Teknol. Inf. Asia, vol. 13, no. 1, pp. 13–22, 2018.
  11. B. R. Jadhavar and T. R. Sontakke, “2.4 GHz Propagation Prediction Models for Indoor Wireless Communications Within Building,” Int. J. Soft Comput. Eng., vol. 2, no. 3, pp. 108–113, 2012.
  12. A. R. Sandeep, Y. Shreyas, S. Seth, R. Agarwal, and G. Sadashivappa, “Wireless Network Visualization and Indoor Empirical Propagation Model for a Campus WI-FI Network,” World Acad. Sci. Eng. Technol., no. August 2008, pp. 730–734, 2009.
  13. D. Akin et al., Certified Wireless Network Administrator Official Study Guide. Bremen Georgia: Planet3 Wireless Inc., 2002.
  14. M. A. Amanaf, E. S. Nugraha, and D. Kurnianto, “Analisis Simulasi Model COST-231 Multiwall Pathloss Indoor Berbasis Wireless Sensor Network pada Aplikasi Absensi Mahasiswa dengan Tag RFID Menggunakan RPS (Radiowave Propagation Simulator),” Bul. Pos dan Telekomun., vol. 16, no. 1, p. 17, 2018.
  15. Wikipedia Contributor, “ITU Model for Indoor Attenuation,” Wikipedia. 2018.
  16. J. Butler et al., Wireless Networking in the Developing World, 3rd Editio. Copenhagen: BbookSprint, 2013.
  17. L. TP-Link Technologies Co, “Access Point TL-WA701ND Specification,” 2019. [Online]. Available: https://www.tp-link.com/id/home-networking/access-point/tl-wa701nd/#specifications.
  18. L. TP-Link Technologies Co, “Access Point Archer C7 Specification.” 2019.
  19. Ubiquiti Networks, “UniFi DataSheet.” Ubiquiti Nteworks, Inc., pp. 1–6.
  20. Y. Chapre, P. Mohapatra, S. Jha, and A. Seneviratne, “Received Signal Strength Indicator and Its Analysis in a Typical WLAN System (Short Paper),” in IEEE Conference on Local Computer Networks, 2013, pp. 304–307.