Devising a technique to evaluate fluctuations in the main parameters of a wireless channel of the 802.11 standard

Authors

DOI:

https://doi.org/10.15587/1729-4061.2020.218720

Keywords:

wireless channel, 802.11 standard, effective speed of information transfer, signal strength, fluctuations, statistical relation

Abstract

This paper reports the technique devised to evaluate fluctuations in the main parameters for a wireless channel of the 802.11 standard based on the confidence regression interval. Underlying such a technique is the use of mathematical ratios of the relationship among the statistical probability, variance, and fluctuation level. It should be noted that this technique could be used when technically diagnosing the 802.11x standard wireless networks at the stages of their design and operation. Applying the proposed technique for the estimation models of the main channel parameters makes it possible to derive an estimate of fluctuation intervals without the need to process large arrays of measurement results. This greatly reduces the time of obtaining the result from diagnosing by involving monitoring algorithms.

An expression for the statistical relation between fluctuations in the main parameters of the 802.11 standard wireless channel was obtained on the basis of the proposed mathematical ratios, which makes it possible to evaluate fluctuations of the information parameter based on the fluctuations of an energy one and vice versa. This is relevant when assessing the effective speed of information transmission based on measuring the signal strength at the receiver input using monitoring algorithms.

The analysis of the reported results and their comparison with empirical studies have shown that based on the interrelation between the main channel parameters with a regression confidence interval it is possible to determine the level of fluctuations based on the confidence probability. The dependence of a fluctuation level on the variances and confidence intervals of regression models has also been established. With a probability of 0.85, the fluctuations have been obtained for direct visibility and at a minimum number of interferences while a probability of 0.97 shows the impact of a multipath wave propagation factor in the premises

Author Biography

Dmytro Mykhalevskiy, Vinnytsia National Technical University Khmelnytske highway, 95, Vinnytsia, Ukraine, 21021

PhD, Associate Professor

Department of Telecommunication Systems and Television

References

  1. Selinis, I., Katsaros, K., Allayioti, M., Vahid, S., Tafazolli, R. (2018). The Race to 5G Era; LTE and Wi-Fi. IEEE Access, 6, 56598–56636. doi: https://doi.org/10.1109/access.2018.2867729
  2. Šljivo, A., Kerkhove, D., Tian, L., Famaey, J., Munteanu, A., Moerman, I. et. al. (2018). Performance Evaluation of IEEE 802.11ah Networks With High-Throughput Bidirectional Traffic. Sensors, 18 (2), 325. doi: https://doi.org/10.3390/s18020325
  3. Ausaf, A., Khan, M. Z., Javed, M. A., Bashir, A. K. (2020). WLAN Aware Cognitive Medium Access Control Protocol for IoT Applications. Future Internet, 12 (1), 11. doi: https://doi.org/10.3390/fi12010011
  4. Mykhalevskiy, D. V. (2019). Investigation of Wireless Channels of 802.11 Standard in the 5ghz Frequency Band. Latvian Journal of Physics and Technical Sciences, 56 (1), 41–52. doi: https://doi.org/10.2478/lpts-2019-0004
  5. Rathod, K., Vatti, R., Nandre, M. (2017). Optimization of Campus Wide WLAN. International Journal of Electrical Electronics & Computer Science Engineering, 4 (5). Available at: https://www.ijeecse.com/V4N5-001.pdf
  6. Chapre, Y., Mohapatra, P., Jha, S., Seneviratne, A. (2013). Received signal strength indicator and its analysis in a typical WLAN system (short paper). 38th Annual IEEE Conference on Local Computer Networks. doi: https://doi.org/10.1109/lcn.2013.6761255
  7. Wang, Y., Li, M., Li, M. (2017). The statistical analysis of IEEE 802.11 wireless local area network–based received signal strength indicator in indoor location sensing systems. International Journal of Distributed Sensor Networks, 13 (12), 155014771774785. doi: https://doi.org/10.1177/1550147717747858
  8. Mardeni, R., Anuar, K., Salamat, A. R., Yusop, M. G. I. (2016). Investigation of ieee 802.11ac signal strength performance in WIFI communication system. International Journal of Electrical, Electronics and Data Communication, 4 (11), 27–31. Available at: http://www.iraj.in/journal/journal_file/journal_pdf/1-312-148128517727-31.pdf
  9. Dhawankar, P., Le-Minh, H., Aslam, N. (2018). Throughput and Range Performance Investigation for IEEE 802.11a, 802.11n and 802.11ac Technologies in an On-Campus Heterogeneous Network Environment. 2018 11th International Symposium on Communication Systems, Networks & Digital Signal Processing (CSNDSP). doi: https://doi.org/10.1109/csndsp.2018.8471865
  10. Rochim, A. F., Sari, R. F. (2016). Performance comparison of IEEE 802.11n and IEEE 802.11ac. 2016 International Conference on Computer, Control, Informatics and Its Applications (IC3INA). doi: https://doi.org/10.1109/ic3ina.2016.7863023
  11. Liu, J., Aoki, T., Li, Z., Pei, T., Choi, Y., Nguyen, K., Sekiya, H. (2020). Throughput Analysis of IEEE 802.11 WLANs with Inter-Network Interference. Applied Sciences, 10 (6), 2192. doi: https://doi.org/10.3390/app10062192
  12. Mykhalevskiy, D. (2020). Development of a method for assessing the effective information transfer rate based on an empirical model of statistical relationship between basic parameters of the Standard 802.11 wireless channel. Eastern-European Journal of Enterprise Technologies, 5 (9 (107)), 26–35. doi: https://doi.org/10.15587/1729-4061.2020.213834
  13. Kurz-Kim, J.-R., Loretan, M. (2007). A Note on the Coefficient of Determination in Models with Infinite Variance Variables. International Finance Discussion Paper, 2007 (895), 1–32. doi: https://doi.org/10.17016/ifdp.2007.895
  14. Sarstedt, M., Mooi, E. (2014). Regression Analysis. Springer Texts in Business and Economics, 193–233. doi: https://doi.org/10.1007/978-3-642-53965-7_7
  15. Cai, T. T., Guo, Z. (2017). Confidence intervals for high-dimensional linear regression: Minimax rates and adaptivity. The Annals of Statistics, 45 (2), 615–646. doi: https://doi.org/10.1214/16-aos1461
  16. Van Wieringen, W. N. (2020). Lecture notes on ridge regression. arXiv. Available at: https://arxiv.org/pdf/1509.09169
  17. Mykhalevskiy, D. V. (2020). Method for estimating the effective data rate in 802.11 channels by using a monitoring algorithm. Journal of Applied Research and Technology, 18 (3). doi: https://doi.org/10.22201/icat.24486736e.2020.18.3.1089
  18. Mykhalevskiy, D. M., Kychak, V. M. (2019). Development of Information Models for Increasing the Evaluation Efficiency of Wireless Channel Parameters of 802.11 Standard. Latvian Journal of Physics and Technical Sciences, 56 (5), 22–32. doi: https://doi.org/10.2478/lpts-2019-0028
  19. Carpenter, T., Bartz, R., Granados, A. et. al. (2018). CWAP-403 Certified Wireless Analysis Professional (Black & White): Study and Reference Guide. Certitrek Publishing, 460.
  20. Perahia, E., Stacey, R. (2013). Next Generation Wireless LANs: 802.11n and 802.11ac. Cambridge University Press. doi: https://doi.org/10.1017/cbo9781139061407

Downloads

Published

2020-12-31

How to Cite

Mykhalevskiy, D. (2020). Devising a technique to evaluate fluctuations in the main parameters of a wireless channel of the 802.11 standard. Eastern-European Journal of Enterprise Technologies, 6(9 (108), 18–24. https://doi.org/10.15587/1729-4061.2020.218720

Issue

Vol. 6 No. 9 (108) (2020): Information and controlling system

Section

Information and controlling system

License

Copyright (c) 2020 Dmytro Mykhalevskiy

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.

A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.