Evaluation of WATERMARK Channel for Underwater Communication using Dual Tree Complex Wavelet Transform based Orthogonal Frequency Division Multiplexing Model

Evaluation of WATERMARK Channel for Underwater Communication using Dual Tree Complex Wavelet Transform based Orthogonal Frequency Division Multiplexing Model

Автор: Girish Nanjareddy, Veena M. Boregowda, Naeem Maroof

Журнал: International Journal of Computer Network and Information Security @ijcnis

Статья в выпуске: 6 vol.15, 2023 года.

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Underwater communication is one of the important research areas which involves design and development of communication systems that can demonstrate high data rate and low Bit Error Rate (BER). In this work three different modulation schemes are compared for their performances in terms of BER and Peak to Average Power Ratio (PAPR). The realistic channel model called WATERMARK is used as a benchmark to evaluate channel performances. The mathematical model is developed in MATLAB and channel environments such as Norway Oslo fjord (NOF1), Norway Continental Shelf (NCS1), Brest Commercial Harbour (BCH1), Kauai (KAU1, KAU2) are considered for modelling different underwater channels. The data symbols are modulated using Dual Tree Complex Wavelet Transform (DTCWT) Orthogonal Frequency Division Multiplexing (OFDM) model to generate multi subcarriers and are demodulated at the receiver considering underwater channel environments. The BER results are evaluated for channel depth less than 10m and 10-50m. An improvement of 2x10-2 in terms of BER is observed when compared with Fast Fourier Transform (FFT) based OFDM model.

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Underwater Acoustic Communication, WATERMARK, Complex Wavelet, OFDM, BER, PAPR

Короткий адрес: https://sciup.org/15018807

IDR: 15018807   |   DOI: 10.5815/ijcnis.2023.06.02

Список литературы Evaluation of WATERMARK Channel for Underwater Communication using Dual Tree Complex Wavelet Transform based Orthogonal Frequency Division Multiplexing Model

  • Daniel, R.L., Lívio C.S., Vicente A.S., ‘Multicarrier Systems Over Underwater Acoustic Channels: A Performance Evaluation,’ Wireless Personal Communications: An International Journal, Vol. 117, No. 2, 2021, pp. 1537–1555.
  • Berger, C. R., Wang, Z., Huang, J. and Zhou, S., ‘Application of compressive sensing to sparse channel estimation,’ IEEE Comm. Mag., Vol. 48, No. 11, 2010, pp. 164–174.
  • Ou, H., Allen, J. and Syrmos, V., ‘Frame-Based Time-Scale Filters for Underwater Acoustic Noise Reduction,’ IEEE J. Ocean. Eng., Vol. 36, No. 2, 2011, pp. 285–297.
  • Lottici, V., Reggiannini, R., and Carta, M., ‘Pilot-Aided Carrier Frequency Estimation for Filter-Bank Multicarrier Wireless Communications on Doubly-Selective Channels,’ IEEE Trans. Sig. Proc., Vol. 58, No. 5, 2010, pp. 2783–2794.
  • Baig, S. and Mughal, H. J., ‘Multirate signal processing techniques for high-speed communication over power lines,’ IEEE Comm. Mag., Vol. 47, No. 1, 2009, pp. 70–76.
  • Hirakawa, K. and Wolfe, P., ‘Rewiring Filterbanks for Local Fourier Analysis: Theory and Practice,’ IEEE Trans. Inf. Theory, Vol. 57, No. 8, 2011, pp. 5360–5374.
  • Marwa, C., Jacques, P., Remi, G., Faouzi, B., ‘Adaptive Wavelet Packet Modulation,’ IEEE Transactions on Communications, Vol. 66, No. 7, 2019, pp. 2947 - 2957.
  • Tiantian, G., Tongpo, Z., Enggee, L., Miguel, L.B., ‘A Review of Wavelet Analysis and Its Applications: Challenges and Opportunities,’ IEEE Access, Vol. 10, 2022, pp. 58869 – 58903.
  • Kingsbury, N.G., ‘The dual-tree complex wavelet transform: A new technique for shift invariance and directional filters,’ in Proc. 8th IEEE DSP Workshop, Utah, Aug. 9–12, paper No. 86,1998.
  • Selesnick, I. W., ‘The Double Density Dual-Tree DWT,’ IEEE Transactions on Signal Processing, Vol. 5, No. 52, 2004, pp. 1304 – 1315.
  • Nerma, M. H. M., Kamel, N. S. and Jagadish, V. J., ‘Investigation of Using Dual Tree Complex Wavelet Transform (DTCWT) to Improve the Performance of OFDM System,’ Engineering Letters, Vol. 20, No. 2, 2012
  • Girish Nanjareddy, Veena, M. B. and Cyril Prasanna., ‘Low Power Area Optimum Configurable 160 to 2560 Subcarrier Orthogonal Frequency Division Multiplexing Modulator-Demodulator Architecture based on Systolic Array and Distributive Arithmetic Look-Up Table,’ Journal of Microelectronics, Electronic Components and Materials (MIDEM), Vol. 51, No. 2, 2021 pp. 119 – 134.
  • Trubuil, J., Goalic, A. and Beuzelin, N., ‘Synchronization and channel coding in shallow water acoustic communication,’ in Proc. OCEANS (Quebec, Canada), 2008, pp. 1–5.
  • Shahzad Ashraf, Sehrish Saleem, Tauqeer Ahmed, " Sagacious Communication Link Selection Mechanism for Underwater Wireless Sensors Network ", International Journal of Wireless and Microwave Technologies, Vol.10, No.4, pp. 22-33, 2020.
  • Kenneth V. Mackenzie, ‘Nine –term equation for Sound speed in the oceans,’ The Journal of the Acoustical Society of America,” Vol. 70, No. 3, 1981, pp. 807-812.
  • Jornet, J.M. AUVNetSim: A Simulator for Underwater Acoustic Networks.
  • Xie G., Gibson J., ‘Incorporating Realistic Acoustic Propagation Models in Simulation of Underwater Acoustic Networks: A Statistical Approach,’ Proceedings of MTS/IEEE Oceans Conference, 2006, pp. 18-21.
  • Harris III, Albert F., ‘Modelling the Underwater Acoustic Channel in Network Simulation,’ NSTOOLS, OCT 22, 2007.
  • Robert J. Urick (1983). Principles of Underwater Sound,” 3rd ed. New York: McGraw-Hill.
  • Socheleau, F.-X., Laot, C.and Passerieux, J.-M., ‘Stochastic replay of non-WSSUS underwater acoustic communication channels recorded at sea,, IEEE Trans. Signal Process., Vol. 59, No. 10, 2011, pp. 4838–4849.
  • Dol, H. S., Colin, M. E. G. D., Ainslie, M. A., van Walree, P. A. and Janmaat, J., ‘Simulation of an underwater acoustic communication channel characterized by wind-generated surface waves and bubbles,’ IEEE J. Ocean. Eng., Vol. 38, No. 4, 2013, pp. 642–654.
  • Van Walree, P.A., ‘The Watermark Benchmark for Underwater Acoustic Modulation Schemes,’ IEEE Journal of Oceanic Engineering, Vol. 42, No. 4, 2017, pp. 1007– 1018.
  • Otnes, R., van Walree, P. A. and Jenserud, T., ‘Validation of replay-based underwater acoustic communication channel simulation,’ IEEE J. Ocean. Eng., Vol. 38, No. 4, 2013, pp. 689–700.
  • https://www.tib.eu/en/search/id/BLCP%3ACN082319291/Kauai-Acomms-MURI-2011-KAM11-Experiment.
  • Van Walree, P. A., Jenserud, T. and Smedsrud, M., ‘A discrete-time channel simulator driven by measured scattering functions,’ IEEE J. Sel. Areas Commun., Vol. 26, No. 9, 2008, pp. 1628–1637.
  • Isukapalli, Y., Song, H. C. and Hodgkiss, W. S., ‘Stochastic channel simulator based on local scattering functions,’ The Journal of the Acoustical Society of America, Vol. 130, No. 4, 2011, pp. 200–205.
  • Van Walree, P. A. and Otnes, R., ‘Ultrawideband underwater acoustic communication channels,’ IEEE Journal of Oceanic Engineering, Vol. 38, No. 4, 2013, pp. 678–688.
  • Potter, J., Alves, J., Green, D., Zappa, G., Nissen, I. and McCoy, K., ‘The JANUS Underwater Communications Standard,’ Proceedings of the 2014 Underwater Communications and Networking (UComms), 2014
  • McCoy, K., Tomasi, B. and Zappa, G., ‘JANUS: The Genesis, Propagation and use of an Underwater Standard V0.98,’ Proceedings of the 10th European Conference on Underwater Acoustics (ECUA), Istanbul, Turkey, 2010
  • Ahmed, M. S., Shah, N. S. M., Aboosi, Y. Y., Gismalla, M. S. M., Abdullah, M. F. L., Jawhar Y. A., and Balfaqih, M., ‘Filter orthogonal frequency-division multiplexing scheme based on polar code in underwater acoustic communication with non-Gaussian distribution noise,’ ETRI Journal, Vol. 43, No. 2, 2020, pp.184–196.
  • Chitre, M., Potter, J. R., and Ong, S. H., ‘Viterbi Decoding of Convolutional Codes in Symmetric α-Stable Noise,’ IEEE Transactions on Communications, vol. 55, 2007.
  • Reza, B., Solmaz, N., Balasubramaniam, N. and Alexei, V., ‘Intermittently Nonlinear Impulsive Noise Mitigation and Doppler Shift Compensation in UWA-OFDM Systems,’ IEEE Access, Vol.7, 2019, pp 36590-36599.
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