Features of Building Wireless Computer Networks to Increase Noise Immunity

2024;
: pp. 170 - 174
1
Lviv Polytechnic National University
2
Lviv Polytechnic National University, Ukraine

The paper analyzes existing types of wireless computer networks, technologies, standards, and potential types of interference. Based on this analysis, a classification of wireless information transmission methods has been proposed, taking into account their parameters and task specificity. The primary issues affecting interference resistance in wireless networks have been highlighted. Technical features, advantages, and limitations of each type have been examined, along with their suitability for various scenarios and operational environments. Additionally, the paper offers an overview of innovative trends and emerging research areas aimed at enhancing interference resistance in the rapidly evolving field of wireless network technology.

  1. L. Stosic, S. Dermendzhieva, L. Tomczyk (2020). “Information and communication technologies  as  a source of education,” World Journal on Educational Technology: Current Issues, 12(2), 128-135. DOI: https://doi.org/10.18844/wjet.v12i2.4815.
  2. Pundalik Chavan, Anooja Ali, Ramaprasad H C, Rama- chandra H V, Hari Krishna H, & E G Satish. (2023). Analysis of Wireless Networks: Successful and Failure Existing Technique. In Satyasai Jagannath Nanda & Ra- jendra Prasad Yadav (Eds.), Data Science and Intelligent Computing Techniques (pp. 877-891). SCRS, India. DOI: https://doi.org/10.56155/978-81-955020-2-8-75.
  3. L. Wu et  al.  (2020).  Artificial  Neural  Network Based Path Loss Prediction for Wireless Communication Network. IEEE    Access,    8,    199523-199538.    DOI:https://doi.org/10.1109/ACCESS.2020.3035209.
  4. Y. Zuo, J. Guo, N. Gao, Y. Zhu, S. Jin, & X. Li. (2023). A Survey of Blockchain and Artificial Intelligence for 6G Wireless Communications. IEEE Communications Surveys & Tutorials, 25(4), 2494-2528. DOI: https://doi.org/10.1109/COMST.2023.3315374.
  5. Tarnavskyi Y. A., Kuzmenko I. M. Organisation of computer networks. Kyiv: Igor Sikorsky Kyiv Polytechnic Institute, 2018,    p.   259.    Available    at:   https://ela.kpi.ua/server/ api/core/bitstreams/e0a0c843-a57d-4d82-8f42- 0eba294bef1f/content (Accessed: 10/14/2024).
  6. Shukla, S., Meghana, K.M., Manjunath, C.R.,  & Shantosh, N. (2017). Comparison of Wireless Network over Wired Network and Its Type. Int. J. Res. Granthaalayah, 5, 14-20. DOI: https://doi.org/ 10.5281/zenodo.572289.
  7. Jordi Salazar. Wireless networks. Czech Technical University of Prague. Faculty of electrical engineering. ISBN:  978-80-01-06197-8  (Online),  2017.  [Electronic resource].  –  Available  at:  https://upcommons.upc.edu/ bitstream/handle/2117/110811/LM01_F_EN.pdf (Accessed: 10/14/2024).
  8. Wireless     Network    Interference     and     Optimization. [Electronic                  resource].                –                             Available at: https://interferencetechnology.com/wireless-network- interference-and-optimization/ (Accessed: 10/14/2024).
  9. User’s and developer’s manual  of  BitSimulator. [Electronic resource]. – Available at: http:// eugen.dedu.free.fr/bitsimulator/manual.pdf (Accessed: 10/14/2024).
  10. H. Mabed. (2017). Enhanced spread in time on-off keying technique for dense Terahertz nanonetworks. In 2017 IEEE Symposium on Computers and Communications (ISCC), Heraklion, Greece, 710-716. DOI: https://doi.org/10.1109/ISCC.2017.8024611.
  11. Yeh, T.-CJ., Dong, Y., & Ye, S. (2023). Molecular Diffusion. In An Introduction to Solute Transport in Heterogeneous Geologic Media (pp. 93-122). Cambridge University Press. DOI: https://doi.org/10.1017/ 9781009049511.005.
  12. J. Wang, X. Liu, M. Peng, & M. Daneshmand. (2020). Performance Analysis of D-MoSK Modulation in Mobile Diffusive-Drift Molecular  Communications. IEEE Internet of Things Journal, 7(11), 11318-11326. DOI: https://doi.org/10.1109/JIOT.2020.2997372.
  13. B. C. Akdeniz, A. E. Pusane, & T. Tugcu. (2018). Position-based modulation in molecular communi- cations. Nano Communication Networks, 16, 60-68. DOI: https://doi.org/10.1016/j.nancom.2018.01.004.
  14. M. Hernandez, R. Kohno, T. Kobayashi, & M. Kim. (2022). New Revision of IEEE 802.15.6 Wireless Body Area Networks. 2022 IEEE 16th International Symposium on Medical Information and Communication Technology (ISMICT), Lincoln, NE, USA, 1-5. DOI: https://doi.org/10.1109/ISMICT56646.2022.9828139.
  15. Park, K., Baek, J., Kim, S., Jeong, M., & Kim, Y. (2019). Touch-Based Dual-Band System Combined  Human Body Communication and Wireless LAN for Wearable Devices. Electronics, 8, 335. DOI: https://doi.org/ 10.3390/electronics8030335.
  16. N. Choudhury, R. Matam, M. Mukherjee, & J. Lloret. (2020).   A   Performance-to-Cost   Analysis   of   IEEE 802.15.4 MAC With 802.15.4e MAC Modes. IEEE Access, 8, 41936-41950. DOI: https://doi.org/10.1109/ ACCESS.2020.2976654.
  17. Telecommunications Signals & Systems Lab Equipment. [Electronic    resource].                –              Available at: https://tecnoedu.com/Download/Emona-TIMS- curriculum_background-r1.pdf (Accessed: 10/14/2024).
  18. D. Verma et al. (2020). A Design of 8 fJ/Conversion-Step 10-bit 8MS/s Low Power Asynchronous SAR ADC for IEEE 802.15.1 IoT Sensor Based Applications. IEEE Access, 8, 85869-85879. DOI: https://doi.org/10.1109/ ACCESS.2020.2992750.
  19. DongFeng Fang, Yi Qian, & Rose Qingyang Hu. (2024). Introduction to 5G Wireless Systems. In 5G Wireless Network Security and Privacy (pp. 1-6). IEEE. DOI: https://doi.org/10.1002/9781119784340.ch1.
  20. C Deng  et  al.  (2020).  IEEE  802.11be  Wi-Fi  7: New Challenges and Opportunities. IEEE Communications Surveys & Tutorials, 22(4), 2136-2166. DOI: https://doi.org/10.1109/COMST.2020.3012715.
  21. Behnam Kamali. (2018). The IEEE 802.16 Standards and the   WiMAX   Technology.   In AeroMACS:   An   IEEE 802.16 Standard-Based Technology for the Next Generation of Air Transportation Systems (pp. 189-258). IEEE. DOI: https://doi.org/10.1002/9781119281139.ch5.
  22. D. M. Molla, H. Badis, L. George, & M. Berbineau. (2022). Software Defined Radio Platforms for Wireless Technologies. IEEE Access, 10, 26203-26229. DOI: https://doi.org/10.1109/ACCESS.2022.3154364.