Skip to main content
SpringerLink
Log in

Transmission Losses Due to Surface Reflections in Deep Water for Multipath Model

  • Conference paper
  • First Online:
Cognitive Computing and Cyber Physical Systems (IC4S 2023)

Abstract

There are several factors which introduces transmission losses in deep water such as: surface reflections; surface ducts; bottom bounce; convergence zones; deep sound channel; reliable acoustic path; and ambient noise. Hence, it is crucial to model the acoustic channel characteristics and evaluate the effect of transmission losses by considering aforementioned factors inorder to employ the network for specific application. This study primarily aims to estimate the transmission losses caused by surface reflections in deep water environments using a multipath acoustic channel model. The simulation is conducted, considering the impact of absorption, sound speed, temperature, and salinity. The depth of the network scenario is varied to analyze the effects of these factors on the transmission losses. It is evident from simulation results, the acoustic velocity increased by 250 m/s when the depth varies from 100 m to 7000 m and temperature decreased from 30 ℃ to 4 ℃. Similarly, when the salinity increased from 30 ppt to 35 ppt, the acoustic velocity has been increased by 7.14% in deep water. An increase in transmission loss of 5 dB has been attained when the wind speed (W) increased from 4 m/s to 12.5 m/s. Similarly, the transmission losses are increased by 8 dB when the angle of incidence (Theta) increased from 20° to 30°.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Sozer, E.M., Stojanovic, M., Proakis, J.G.: Underwater acoustic networks. IEEE J. Ocean. Eng. 25(1), 72–83 (2000)

    Article  Google Scholar 

  2. Akyildiz, I.F., Pompili, D., Melodia, T.: Underwater acoustic sensor networks: research challenges. Ad Hoc Netw. 3(3), 257–279 (2005)

    Article  Google Scholar 

  3. Venkateswara Rao C., Padmavathy, N.: Effect of link reliability and interference on two-terminal reliability of mobile ad hoc network. In: Advances in Data Computing, Communication and Security. Lecture Notes on Data Engineering and Communications Technologies, vol. 106, pp. 555–565 (2022)

    Google Scholar 

  4. Rao, C.V., Padmavathy, N., Chaturvedi, S.K.: Reliability evaluation of mobile ad hoc networks: with and without interference. In: IEEE 7th International Advance Computing Conference, pp. 233–238 (2017)

    Google Scholar 

  5. Barbeau, M., Garcia-Alfaro, J., Kranakis, E., Porretta, S.: The sound of communication in underwater acoustic sensor networks: (position paper). In: Ad Hoc Networks: 9th International Conference, AdHocNets Niagara Falls, ON, Canada, pp. 13–23 (2017)

    Google Scholar 

  6. Akyildiz, I.F., Pompili, D., Melodia, T.: Challenges for efficient communication in under-water acoustic sensor networks. ACM SIGBED Rev. Spec. Issue Embed. Sens. Netw. Wirel. Comput. 1(2), 3−8 (2004)

    Google Scholar 

  7. Stojanovic, M., Preisig, J.: Underwater acoustic communication channels: propagation models and statistical characterization. IEEE Commun. Mag. 47(1), 84–89 (2009)

    Article  Google Scholar 

  8. Jindal, H., Saxena, S., Singh, S.: Challenges and issues in underwater acoustics sensor networks: a review. In: International Conference on Parallel, Distributed and Grid Computing Solan, pp. 251–255 (2014)

    Google Scholar 

  9. Ismail, N.S.N., Hussein, L., Syed, A., Hafizah, S.: Analyzing the performance of acoustic channel in underwater wireless sensor network. In: Asia International Conference on Modelling & Simulation, pp. 550–555 (2010)

    Google Scholar 

  10. Wanga, X., Khazaiec, S., Chena, X.: Linear approximation of underwater sound speed profile: precision analysis in direct and inverse problems. Appl. Acoust. 140, 63–73 (2018)

    Article  Google Scholar 

  11. Ali, M.M., Sarika, J., Ramachandran, R.: Effect of temperature and salinity on sound speed in the central Arabian sea. Open Ocean Eng. J. 4, 71–76 (2011)

    Google Scholar 

  12. Kumar, S., Prince, S., Aravind, J.V., Kumar, G.S.: Analysis on the effect of salinity in underwater wireless optical communication. Mar. Georesour. Geotechnol. 38(3), 291–301 (2020)

    Article  Google Scholar 

  13. Preisig, J.: Acoustic propagation considerations for underwater acoustic communications network development. Mob. Comput. Commun. Rev. 11(4), 2–10 (2006)

    Article  Google Scholar 

  14. Sehgal, A., Tumar, I., Schonwalder, J.: Variability of available capacity due to the effects of depth and temperature in the underwater acoustic communication channel. In: Oceans 2009-Europe, Bremen, pp. 1–6 (2009)

    Google Scholar 

  15. Leroy, C.C., Parthiot, F.: Depth-pressure relationships in the oceans and seas. J. Acoust. Soc. Am. 103(3), 1346–1352 (1998)

    Article  Google Scholar 

  16. Yuwono, N.P., Arifianto, D., Widjiati, E., Wirawan.: Underwater sound propagation characteristics at mini underwater test tank with varied salinity and temperature. In: 6th International Conference on Information Technology and Electrical Engineering (ICITEE), pp. 1–5 (2014)

    Google Scholar 

  17. Shi, H., Kruger, D., Nickerson, J.V.: Incorporating environmental information into underwater acoustic sensor coverage estimation in estuaries. In: MILCOM 2007 - IEEE Military Communications Conference, pp. 1–7 (2007)

    Google Scholar 

  18. Morozs, N., Gorma, W., Henson, B.T., Shen, L., Mitchell, P.D., Zakharov, Y.V.: Channel modeling for underwater acoustic network simulation. IEEE Access 8, 136151–136175 (2020)

    Article  Google Scholar 

  19. Lee, H.K., Lee, B.M.: An underwater acoustic channel modeling for Internet of Things networks. Wireless Pers. Commun. 116(3), 2697–2722 (2020). https://doi.org/10.1007/s11277-020-07817-x

    Article  Google Scholar 

  20. Onasami, O., Feng, M., Xu, H., Haile, M., Qian, L.: Underwater acoustic communication channel modeling using reservoir computing. IEEE Access 10, 56550–56563 (2022)

    Article  Google Scholar 

  21. Zhu, X., Wang, C.X., Ma, R.: A 2D non-stationary channel model for underwater acoustic communication systems. In: IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), pp. 1–6 (2021)

    Google Scholar 

  22. Kotipalli, P., Vardhanapu, P.: Frame boundary detection and deep learning-based doppler shift estimation for FBMC/OQAM communication system in underwater acoustic channels. IEEE Access 10, 17590–17608 (2022)

    Article  Google Scholar 

  23. Venkata Lalitha, N., et al.: IoT based energy efficient multipath power control for underwater sensor network. Int. J. Syst. Assur. Eng. Manag. 1–10 (2022)

    Google Scholar 

  24. Sekhar, S., et al.: Effects of water absorption on the mechanical properties of hybrid natural fibre/phenol formaldehyde composites. Sci. Rep. 11(1), 13385 (2021)

    Google Scholar 

  25. Etter, P.C.: Underwater Acoustic Modeling and Simulation. CRC press (2018)

    Google Scholar 

  26. Padmavathy, N., Venkateswara Rao, C.H.: Reliability evaluation of underwater sensor network in shallow water based on propagation model. J. Phys. Conf. Ser. 1921(1), 012018 (2021)

    Google Scholar 

  27. Venkateswara Rao, C., Swathi, S., Charan, P.S.R., Santhosh Kumar, C.V., Pathi, A.M.V., Praveena, V.: Evaluation of sound propagation, absorption, and transmission loss of an acoustic channel model in shallow water. In: Congress on Intelligent Systems, pp. 455–465 (2023)

    Google Scholar 

  28. Padmavathy N., Venkateswara Rao, C.H.: Effect of undersea parameters on reliability of underwater acoustic sensor network in shallow water. In: IOP Conference Series: Materials Science and Engineering, vol. 1272, no. 1, p. 012011 (2022)

    Google Scholar 

  29. Venkateswara Rao, C., et al.: Analysis of acoustic channel model characteristics in deep-sea water. In: International Conference on Cognitive Computing and Cyber Physical Systems, pp. 234–243 (2023)

    Google Scholar 

  30. Venkateswara Rao, C., et al.: Comparison of acoustic channel characteristics in shallow and deep-sea water. In: International Conference on Cognitive Computing and Cyber Physical Systems, pp. 256–266 (2023)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of ECE, GIET Engineering College, Rajahmundry, India

    Veera Venkata Ramana Kandi

  2. Department of ECE, B V Raju Institute of Technology, Narsapur, Medak, India

    Pulugujju Rajesh

  3. Department of ECE, Aditya College of Engineering and Technology, Surampalem, India

    S V Kiranmayi Sridhara

  4. Department of ECE, B V C College of Engineering, Rajamundry, India

    P U V S N Pavan Kumar Nalam

  5. Physics and Electronics Department, B V Raju College, Bhimavaram, India

    B Srinivasa Seshagiri Rao

  6. Department of ECE, Sasi Institute of Technology and Engineering, Tadepalligudem, India

    M Ravi Sankar

  7. Department of ECE, Vishnu Institute of Technology, Bhimavaram, India

    Ch. Venkateswara Rao

Authors
  1. Veera Venkata Ramana Kandi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pulugujju Rajesh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S V Kiranmayi Sridhara
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. P U V S N Pavan Kumar Nalam
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. B Srinivasa Seshagiri Rao
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. M Ravi Sankar
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ch. Venkateswara Rao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ch. Venkateswara Rao .

Editor information

Editors and Affiliations

  1. Vishnu Institute of Technology, Bhimavaram, Andhra Pradesh, India

    Prakash Pareek

  2. Norwegian University of Science and Technology, Gjøvik, Norway

    Nishu Gupta

  3. University of Trás-os-Montes e Alto Douro, Vila Real, Portugal

    M. J. C. S. Reis

Rights and permissions

Reprints and permissions

Copyright information

© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kandi, V.V.R. et al. (2024). Transmission Losses Due to Surface Reflections in Deep Water for Multipath Model. In: Pareek, P., Gupta, N., Reis, M.J.C.S. (eds) Cognitive Computing and Cyber Physical Systems. IC4S 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 537. Springer, Cham. https://doi.org/10.1007/978-3-031-48891-7_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-48891-7_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48890-0

  • Online ISBN: 978-3-031-48891-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation