Vol. 105

Latest Volume
All Volumes
All Issues
2022-07-27

A Standard Ray Tracing Technique for Predicting Signal Strength of Wireless Sensor Network in Smart Building

By Hany M. El-Maghrabi
Progress In Electromagnetics Research Letters, Vol. 105, 79-84, 2022
doi:10.2528/PIERL22052504

Abstract

In this paper, a standard ray tracing model based on Geometrical Optics (GO) is proposed for predicting the signal strength of Wireless Sensor Network (WSN), ZigBee nodes, in an indoor environment. The signal strength is calculated analytically. The results are compared with numerical analysis implemented in FEKO computational electromagnetic software, and agreement is demonstrated. Also, the model is verified by a simple measurement campaign in a straight corridor section of commercial building, and results agreement is obtained. The results show that the proposed technique is capable of predicting the signal strength of WSN sensors in a corridor section of indoor environment with good accuracy, fast calculation time, and low computational resources and complexity. The proposed analytical model and measurement dataset can help WSN designers select the best locations of ZigBee nodes in a straight corridor section with good signal quality.

Citation


Hany M. El-Maghrabi, "A Standard Ray Tracing Technique for Predicting Signal Strength of Wireless Sensor Network in Smart Building," Progress In Electromagnetics Research Letters, Vol. 105, 79-84, 2022.
doi:10.2528/PIERL22052504
http://test.jpier.org/PIERL/pier.php?paper=22052504

References


    1. Sasipriya, S., R. Gurupriya, B. Ilakkiya, and J. S. Kaavya, "IOT enabled smart home and health monitoring system," 6th International Conference on Communication and Electronics Systems (ICCES), 573-576, Jul. 2021.

    2. Samijayani, O. N. and A. M. Muthiah, "Wireless sensor network performance evaluation on building with ZigBee transmission," International Conference on Smart Computing and Electronic Enterprise (ICSCEE), 1-6, Jul. 2018.

    3. Lan, L. and Y. K. Tan, "Advanced building energy monitoring using wireless sensor integrated energy plus platform for personal climate control," IEEE International Conference on Power Electronics and Drive Systems, 567-574, Aug. 2015.

    4. Ciuonzo, D., P. S. Rossi, and P. Willett, "Generalized rao test for decentralized detection of an uncooperative target," IEEE Signal Processing Letters, Vol. 24, No. 5, 678-682, May 2017.
    doi:10.1109/LSP.2017.2686377

    5. Niu, R. and P. K. Varshney, "Performance analysis of distributed detection in a random sensor field," IEEE Transactions on Signal Processing, Vol. 56, No. 1, 339-349, Jan. 2008.
    doi:10.1109/TSP.2007.906770

    6. Ciuonzo, D., P. S. Rossi, and P. K. Varshney, "Distributed detection in wireless sensor networks under multiplicative fading via generalized score tests," IEEE Internet of Things Journal, Vol. 8, No. 11, 9059-9071, Jun. 1, 2021.
    doi:10.1109/JIOT.2021.3056325

    7. Danbatta, S. J. and A. Varol, "Comparison of Zigbee, Z-wave, Wi-Fi, and bluetooth wireless technologies used in home automation," 2019 7th International Symposium on Digital Forensics and Security (ISDFS), 1-5, 2019.

    8. Lee, J., Y. Su, and C. Shen, "A comparative study of wireless protocols: bluetooth, UWB, ZigBee, and Wi-Fi," IECON 2007 --- 33rd Annual Conference of the IEEE Industrial Electronics Society, 46-51, 2007.
    doi:10.1109/IECON.2007.4460126

    9. Kuzminykh, I., A. Snihurov, and A. Carlsson, "Testing of communication range in ZigBee technology," IEEE International Conference on the Experience of Designing and Application of CAD Systems (CADSM), 133-136, Feb. 2017.

    10. Jawad, H. M., et al., "Accurate empirical path-loss model based on particle swarm optimization for wireless sensor networks in smart agriculture," IEEE Sensors Journal, Vol. 20, No. 1, 552-561, Sep. 2020.
    doi:10.1109/JSEN.2019.2940186

    11. Amorim, R., P. Mogensen, T. Sorensen, I. Z. Kovács, and J. Wigard, "Pathloss measurements and modeling for UAVs connected to cellular networks," IEEE Vehicular Technology Conference (VTC Spring), 1-6, 2017.

    12. Ning, G., S. Ma, Y. Guo, and Q. Wang, "Prediction of indoor wireless LAN field strength distribution based on ray tracing method," 4th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), 656-6563, Oct. 2019.

    13. Kumar, P. and G. Ranganath, "Geometrical theory of diffraction," Pramana --- J. Phys., Vol. 37, 457-488, 1991.
    doi:10.1007/BF02846778

    14. Akl, R., D. Tummala, and X. Li, "Indoor propagation modeling at 2.4 GHz for IEEE 802.11 Networks," The Six International Muti-Conference on Wireless and Optical Communication, Jul. 2006.

    15. The MathWorks Inc., "MATLAB,", http://www.mathworks.com.

    16. FEKO Suite, "Altair Engineering,", 2021.

    17. Gharghan, S. K., R. Nordin, M. Ismail, and J. A. Ali, "Accurate wireless sensor localization technique based on hybrid PSO-ANN algorithm for indoor and outdoor track cycling," IEEE Sensors Journal, Vol. 16, 529-541, Jan. 2016.
    doi:10.1109/JSEN.2015.2483745

    18. Digi International, , https://www.digi.com/xbee.