Investigation of Parameters Affecting Underwater Communication Channel | Journal of Engineering Sciences

Investigation of Parameters Affecting Underwater Communication Channel

Author(s): Aydin S., Onur T. O.*

Affiliation(s):  Zonguldak Bulent Ecevit University, 67100 Zonguldak, Turkey.

*Corresponding Author’s Address: [email protected]

Issue: Volume 7, Issue 1 (2020)

Dates:
Paper received: February 25, 2020
The final version of the paper received: June 3, 2020
Paper accepted online: June 17, 2020

Citation:
Aydin, S., Onur, T. O. (2020). Investigation of parameters affecting underwater communication channel. Journal of Engineering Sciences, Vol. 7(1), pp. F39–E44, doi: 10.21272/jes.2020.7(1).f4

DOI: 10.21272/jes.2020.7(1).f4

Research Area:  CHEMICAL ENGINEERING: Processes in Machines and Devices

Abstract. Underwater communication has become a widely studied area in recent years and showed great potential to be an area of research. Acoustic communication is often preferred in underwater communication due to its suitability for an underwater diffusion environment. However, in underwater communication, the physical and chemical properties of the water environment affect sound propagation. Therefore, determining and examining parameters affecting channel performance in underwater communication plays an essential role in inefficient communication. In this study, the effects of salinity, depth, noise, temperature, and frequency parameters for the underwater channel model are examined. By determining the effects of these parameters on spherical and cylindrical propagation, suitable propagation geometry and parameter values for an efficient channel are investigated. In light of the results obtained, in case of studying in a limited area, the path and absorption losses can be reduced by selecting cylindrical propagation as a geometrical propagation model, thereby an efficient channel model can be formed.

Keywords: cylindrical propagation, spherical propagation, underwater communication channel, acoustic communication, path loss, absorption loss.

References:

  1. Alkama, R., Cescatti, A. (2016). Biophysical climate impacts of recent changes in global forest cover. Science, Vol. 351, pp. 600–604, doi: 10.1126/science.aac8083.
  2. Kirtskhalia, V. (2016). Correct definition of sound speed and its consequences in the task of hydrodynamics. Journal of Fluids, Vol. 2016, pp 1–9, doi: 10.1155/2016/4519201.
  3. Akyildiz, I. F., Pompili, D. and Melodia, T. (2005). Under water acoustic sensor networks: research challenges. Ad Hoc Networks, Vol. 3(3), pp. 257–279, doi: 10.1016/j.adhoc.2005.01.004.
  4. Stajanovic, M. (1996). Recent advances in high rate underwater acoustic communications. IEEE Journal of Oceanic Engineering, Vol. 21(2), pp. 125–136, doi: 10.1109/48.486787.
  5. Catipovic, J. (1990). Performance limitations in underwater acoustic telemetry. IEEE Journal of Oceanic Engineering, Vol. 15(3), pp. 205–216, doi: 10.1109/48.107149.
  6. Kilfoyle, D. B., Baggeroer, A. B. (2000). The state of the art in underwater acoustic telemetry. IEEE Journal of Oceanic Engineering, Vol. 25(1), pp. 4–27, doi: 10.1109/48.820733.
  7. Zhichao, L., Jie, Z., Jiucai, J., Qi, L., Lanjun, L., Pengcheng, Z., Baoru, G. (2018). Underwater acoustic communication quality evaluation model based on USV. Shock and Vibration, Vol. 2018, pp. 1–7, doi: 10.1155/2018/2609073.
  8. Akyildiz, I. F., Pompili, D., Melodia, T. (2005). Underwater acoustic sensor networks: research challenges. Ad-Hoc Networks, Vol. 3(3), pp. 257–279, doi: 10.1016/j.adhoc.2005.01.004.
  9. Mendez, P. A., James, R. (2015). A comparative study of underwater wireless optical communication for three different communication links. IOSR Journal of Electronics and Communication Engineering, Vol. 10(3), pp. 40–48.
  10. Hou, R., He, L., Hu, S., Luo, J. (2018). Energy-balanced unequal layering clustering in underwater acosutic sensor networks. IEEE Access, Vol. 6, pp. 39685–39691, doi: 1109/ACCESS.2018.2854276.
  11. Urick, R. J. (1996). Principles of Underwater Sound, 3rd. ed., McGraw-Hill.
  12. Chen, P., Rong, Y., Nordholm, S., He, Z. Q., Duncan, A. J. (2017). Joint channel estimation and impulsive noise mitigation in underwater acoustic OFDM communication systems. IEEE Transactions on Wireless Communications, Vol. 16(9), pp. 6165–6178, doi: 1109/TWC.2017.2720580.
  13. Domingo, M. C. (2008). Overview of channel models for underwater wireless communication networks. Physical Communication, Vol. 1(3), pp. 163–182, doi: 1016/j.phycom.2008.09.001.
  14. Thorp, W. H. (1967). Analytic description of the low-frequency attenuation coefficient. Journal of the Acoustical Society of America, Vol. 42(1), pp. 270–270, doi: 1121/1.1910566.
  15. Fisher, F., Simmons V. (1977). Sound absorption in seawater. Journal of the Acoustical Society of America, Vol. 61, pp. 1–13, doi: 10.1121/1.2015423.
  16. Francois, R R., Garrison, G. (1982). Sound absorption based on ocean measurements: Part 1. Journal of the Acoustical Society of America, Vol. 72(3), pp. 896–907, doi: 10.1121/1.388673.
  17. Sehgal, A., Tumar, I., Schonwalder, J. (2009). Variability of available capacity due to the effects of depth and temperature in the underwater acoustic communication channel. IEEE Oceans 2009, pp. 1–6, doi: 1109/OCEANSE.2009.5278268.
  18. Ainslie, M. A., McColm, J. G. (1998). A simplified formula for viscous and chemical absorption in seawater. Journal of the Acoustical Society of America, Vol. 103(3), pp. 1671–1672, doi: 1121/1.421258.
  19. Wu, Y. C., Min, R. (2012). Joint channel estimation and data detection for multihop OFDM relaying system under unknown channel orders and doppler frequencies. IEEE Communications Magazine, pp. 97–102.
  20. Lasota, H., Kochanska, I. (2011). Transmission parameters of underwater communication channels. Hydroacoustics, Vol. 14, pp. 119–126.
  21. Coates, R. (1990). Underwater Acoustic Systems, Hong Kong: Macmillan.

Full Text



© 2014-2024 Sumy State University
"Journal of Engineering Sciences"
ISSN 2312-2498 (Print), ISSN 2414-9381 (Online).
All rights are reserved by SumDU