Effect of Underwater Ambient Noise on Quadraphase Phase-shift Keying Acoustic Sensor Network Links in Extremely Low Frequency Band


1 Department of Electrical Engineering, Universiti Teknologi Malaysia (UTM), Skudai, Malaysia

2 Department of Electrical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia


This study evaluates the impact of underwater ambient noise using seven real noise samples; Dolphin, Rain, Ferry, Sonar, Bubbles, Lightning, and Outboard Motor in three frequency ranges in extremely low frequency (ELF) band. The ELF band is the most significant bandwidth for underwater long-range communication. ELF band which is extended from 3 to 3000 Hz clearly, faces bandwidth limitation. Measuring the impact of noises that are imposed on this bandwidth, based on center frequency employment is highly regarded. This measurement optimizes detection process and assists the design of more reliable underwater communication systems and will improve network quality of service (QoS). In this investigation, Quadraphase Phase-shift Keying (QPSK) acoustic communication nodes are designed in MATLAB and real noise samples are added to network link. Three frequency bands are defined (0-1600), (400-2000) and (1600-3200) Hz, then the impact of noise samples on phase is measured. Next, ( ) ratio for every bandwidth (BW) is simulated. The result demonstrates 0 to 1600 Hz band is the nosiest part of the ELF band. This study discovered the Bubble noise sample from the environmental noise; Ferry from man-made noise and the Dolphin in mammal’s noise have the greatest impact on 0 to 1600 Hz bandwidth.


1.     Lurton, X., "An introduction to underwater acoustics: Principles and applications, Springer Science & Business Media,  (2002).

2.     Bahrami, N., Khamis, N.H.H. and Baharom, A., "Evaluation of underwater acoustical intermittent ambient noise", in Signal Processing & Its Applications (CSPA), 11th International Colloquium on, IEEE., (2015), 11-14.

3.     Traverso, F., Vernazza, G. and Trucco, A., "Simulation of non-white and non-gaussian underwater ambient noise", in OCEANS, Yeosu, IEEE., (2012), 1-10.

4.     Kinsler, L.E., Frey, A.R., Coppens, A.B. and Sanders, J.V., "Fundamentals of acoustics", Fundamentals of Acoustics, 4th Edition.,  (1999), 560-569.

5.     Pickard, G.L. and Emery, W.J., "Descriptive physical oceanography: An introduction, Elsevier,  (2016).

6.     Cole, R.H. and Weller, R., "Underwater explosions", Physics Today,  Vol. 1, No., (1948), 35-42.

7.     Lanzagorta, M., "Underwater communications", Synthesis Lectures on Communications,  Vol. 5, No. 2, (2012), 1-129.

8.     Bahrami, N., Khamis, N.H.H. and Baharom, A.B., "Study of underwater channel estimation based on different node placement in shallow water", IEEE Sensors Journal,  Vol. 16, No. 4, (2016), 1095-1102.

9.     Gray, C., Uehara, G. and Lin, S., "Bandwidth efficient modulation for underwater acoustic data-communication", in OCEANS'94.'Oceans Engineering for Today's Technology and Tomorrow's Preservation.'Proceedings, IEEE. Vol. 1, (1994), I/281-I/285 vol. 281.

10.   Freitag, L., Grund, M., Singh, S. and Johnson, M., "Acoustic communication in very shallow water: Results from the 1999 auv fest", in Oceans MTS/IEEE Conference and Exhibition, IEEE. Vol. 3, (2000), 2155-2160.

11.   Choi, Y., Park, J.-w., Kim, S.-M. and Lim, Y.-k., "A phase coherent all-digital transmitter and receiver for underwater acoustic communication systems", in System Theory,. Proceedings of the 35th Southeastern Symposium on, IEEE., (2003), 79-83.

12.   Goalic, A., Trubuil, J. and Beuzelin, N., "Channel coding for underwater acoustic communication system", in OCEANS, IEEE., (2006), 1-4.

13.   Nasri, N., Kachouri, A., Andrieux, L. and Samet, M., "Design considerations for wireless underwater communication transceiver", in Signals, Circuits and Systems,. SCS. 2nd International Conference on, IEEE., (2008), 1-5.

14.   Stojanovic, M. and Preisig, J., "Underwater acoustic communication channels: Propagation models and statistical characterization", IEEE Communications Magazine,  Vol. 47, No. 1, (2009), 84-89.

15.   Labrador, Y., Karimi, M., Pan, D. and Miller, J., "Modulation and error correction in the underwater acoustic communication channel", International Journal of Computer Science and Network Security,  Vol. 9, No. 7, (2009), 123-130.

16.   Ochi, H., Watanabe, Y., Shimura, T. and Hattori, T., "The acoustic communication experiment at 1,600 m depth using qpsk and 8psk", in OCEANS, IEEE., (2010), 1-5.

17.   Yoshida, H., Hyakudome, T., Ishibashi, S., Ochi, H., Asakawa, K., Kasaya, T., Saito, T. and Okamoto, S., "Study on land-to-underwater communication", in Wireless Personal Multimedia Communications (WPMC), 14th International Symposium on, IEEE., (2011), 1-5.

18.   Board, O.S. and Council, N.R., "Ocean noise and marine mammals, National Academies Press,  (2003).

19.   Etter, P.C., "Underwater acoustic modeling and simulation, CRC Press,  (2013).

20.   Hodges, R.P., "Underwater acoustics: Analysis, design and performance of sonar, John Wiley & Sons,  (2011).

21.   Domingo, M.C., "Overview of channel models for underwater wireless communication networks", Physical Communication,  Vol. 1, No. 3, (2008), 163-182.

22.   Kilfoyle, D.B. and Baggeroer, A.B., "The state of the art in underwater acoustic telemetry", IEEE Journal of oceanic engineering,  Vol. 25, No. 1, (2000), 4-27.

23.   Bahrami, N., Khamis, N.H.H., Baharom, A. and Yahya, A., "Underwater channel characterization to design wireless sensor network by bellhop", Telkomnika (Telecommunication Computing Electronics and Control),  Vol. 14, No. 1, (2016), 110-118.

24.   Etter, P.C., "Underwater acoustic modeling: Principles, techniques and application", London and New York: Elsevier Applied Science,  (1991).

25.   Oppenheim, A.V. and Willsky, A.S., With it young, signals and systems. (1983), Prentice Hall.

26.   Arkat, J. and Jafari, R., "Network location problem with stochastic and uniformly distributed demands", International Journal of Engineering-Transactions B: Applications,  Vol. 29, No. 5, (2016), 654-660.

27.   Azami, H., Hassanpour, H. and Anisheh, S., "An improved automatic eeg signal segmentation method based on generalized likelihood ratio", International Journal of Engineering-Transactions A: Basics,  Vol. 27, No. 7, (2014), 1015-1022.

28.   Moshiri, B., Eslambolchi, P. and HoseinNezhad, R., "Fuzzy clustering approach using data fusion theory and its application to automatic isolated word recognition", International Journal of Engineering Transactions B,  Vol. 16, (2003), 329-336.