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Electronics and Telecommunications Research Institute (한국전자통신연구원)
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Filter orthogonal frequency-division multiplexing scheme based on polar code in underwater acoustic communication with non-Gaussian distribution noise

  • Ahmed, Mustafa Sami (Department of Communication Engineering, Universiti Tun Hussein Onn Malaysia) ;
  • Shah, Nor Shahida Mohd (Faculty of Engineering Technology, Universiti Tun Hussein Onn Malaysia) ;
  • Al-Aboosi, Yasin Yousif (Faculty of Engineering, University of Mustansiriyah) ;
  • Gismalla, Mohammed S.M. (Department of Communication Engineering, Universiti Tun Hussein Onn Malaysia) ;
  • Abdullah, Mohammad F.L. (Department of Communication Engineering, Universiti Tun Hussein Onn Malaysia) ;
  • Jawhar, Yasir Amer (Department of Communication Engineering, Universiti Tun Hussein Onn Malaysia) ;
  • Balfaqih, Mohammed (Department of Computer and Network Engineering, University of Jeddah)
  • Received : 2019.12.15
  • Accepted : 2020.05.25
  • Published : 2021.04.15
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Abstract

The research domain of underwater communication has garnered much interest among researchers exploring underwater activities. The underwater environment differs from the terrestrial setting. Some of the main challenges in underwater communication are limited bandwidth, low data rate, propagation delay, and high bit error rate (BER). As such, this study assessed the underwater acoustic (UWA) aspect and explored the expression of error performance based on t-distribution noise. Filter orthogonal frequency-division multiplexing refers to a new waveform candidate that has been adopted in UWA, along with turbo and polar codes. The empirical outcomes demonstrated that the noise did not adhere to Gaussian distribution, whereas the simulation results revealed that the filter applied in orthogonal frequency-division multiplexing could significantly suppress out-of-band emission. Additionally, the performance of the turbo code was superior to that of the polar code by 2 dB at BER 10-3.

Keywords

References

  1. P. Chen et al., Joint channel estimation and impulsive noise mitigation in underwater acoustic OFDM communication systems, IEEE Trans. Wirel. Commun. 16 (2017), 6165-6178. https://doi.org/10.1109/TWC.2017.2720580
  2. M. Chitre, S. Ong, and J. Potter, Performance of coded OFDM in very shallow water channels and snapping shrimp noise, in Proc. OCEANS MTS/IEEE (Washington, DC, USA), Sept. 2005, pp. 996-1001.
  3. R. Gomathi and J. M. L. Manickam, PAPR reduction technique using combined DCT and LDPC based OFDM system for underwater acoustic communication, ARPN J. Eng. Appl. Sci. 11 (2016), 4424-4430.
  4. M. Chitre, J. Potter, and O. S. Heng, Underwater acoustic channel characterisation for medium-range shallow water communications, in Proc. OCEANS'04. MTTS/IEEE TECHNO-OCEAN (Kobe, Japan), Nov. 2004, pp. 40-45.
  5. L. Liu et al., Design and implementation of channel coding for underwater acoustic system, in proc. IEEE Int. Conf. on ASIC (Changsha, China), Oct. 2009, pp. 497-500.
  6. M. S. Ahmed et al., Filtered-OFDM with channel coding based on T-distribution noise for underwater acoustic communication, J. Ambient Intell. Humaniz. Comput. 11 (2020), 1-14.
  7. C. Seo et al., Performance comparison of convolution and Reed-Solomon codes in underwater multipath fading channel, Jpn. J. Appl. Phys. 53 (2014), 07KG02:1-4.
  8. J. Trubuil, A. Goalic, and N. Beuzelin, Synchronization and channel coding in shallow water acoustic communication, in Proc. OCEANS (Quebec, Canada), Sept. 2008, pp. 1-5.
  9. J. Huang, S. Zhou, and P. Willett, Nonbinary LDPC coding for multicarrier underwater acoustic communication, IEEE J. Sel. Area. Comm. 26 (2008), 1684-1696. https://doi.org/10.1109/JSAC.2008.081208
  10. B. Vasic, P. Ivanis, and S. Brkic, Low complexity memory architectures based on LDPC codes: Benefits and disadvantages, in Proc. Telecommun. Modern Satellite, Cable Broadcasting Services (Nis, Serbia), Oct. 2015, pp. 11-18.
  11. L. Liu et al., Channel coding for underwater acoustic single-carrier CDMA communication system, in Proc. Int. Conf. Electron. Inf. Eng. (Nanjing, China), Jan. 2017, pp. 103222S:1-10.
  12. W. Han, J. Huang, and M. Jiang, Performance analysis of underwater digital speech communication system based on LDPC codes, in Proc. IEEE Conf. Ind. Electron. Applicat. (Xian, China), May 2009, pp. 567-570.
  13. Y. A. Jawhar et al., A review of partial transmit sequence for PAPR reduction in the OFDM systems, IEEE Access 7 (2019), 18021-18041. https://doi.org/10.1109/access.2019.2894527
  14. Y. A. Jawhar et al., New low-complexity segmentation scheme for the partial transmit sequence technique for reducing the high PAPR value in OFDM systems, ETRI J. 40 (2018), 699-713. https://doi.org/10.4218/etrij.2018-0070
  15. J. Panaro et al., Underwater acoustic noise model for shallow water communications, in Proc. Brazilian Telecommun. Symp. 2012.
  16. S. Banerjee and M. Agrawal, On the performance of underwater communication system in noise with Gaussian mixture statistics, in Proc. National Conf. Commun. (Kanpur, India), 2014, pp. 1-6.
  17. M. Stojanovic and J. Preisig, Underwater acoustic communication channels: Propagation models and statistical characterization, IEEE Commun. Mag. 47 (2009), 84-89. https://doi.org/10.1109/MCOM.2009.4752682
  18. N. S. M. Shah, Y. Y. Al-Aboosi, and M. S. Ahmed, Error performance analysis in underwater acoustic noise with non-Gaussian distribution, Telkomnika 16 (2018), 681-689. https://doi.org/10.12928/telkomnika.v16i2.8001
  19. Y. Y. Al-Aboosi and A. Z. Sha'ameri, Improved underwater signal detection using efficient time-frequency de-noising technique and Pre-whitening filter, Appl. Acoust. 123 (2017), 93-106. https://doi.org/10.1016/j.apacoust.2017.03.013
  20. J. Panaro et al., Underwater acoustic noise model for shallow water communications, in Brazilian Telecomm. Symp., 2012.
  21. D. Li, Y. Wu, and M. Zhu, Nonbinary LDPC code for noncoherent underwater acoustic communication under non-Gaussian noise, in Proc. IEEE Int. Conf. Signal Process. Commun. Comput. (Xiamen, China), Oct. 2017, pp. 1-6.
  22. A. Goalic, J. Trubuil, and N. Beuzelin, Channel coding for underwater acoustic communication system, in Proc. OCEANS (Boston, MA, USA), Sept. 2006, pp. 1-4.
  23. Y. Y. Al-Aboosi et al., Diurnal variability of underwater acoustic noise characteristics in shallow water, Telkomnika 15 (2017), 314. https://doi.org/10.12928/telkomnika.v15i1.4510
  24. Y. Y. Al-Aboosi and A. Z. Sha'ameri, Improved signal de-noising in underwater acoustic noise using S-transform: A performance evaluation and comparison with the wavelet transform, J. Ocean Eng. Sci. 2 (2017), 172-185. https://doi.org/10.1016/j.joes.2017.08.003
  25. M. Ahsanullah, B. G. Kibria, and M. Shakil, Normal and student's T distributions and their applications, Springer, Paris, Netherlands, 2014.
  26. Y. A. Al-Jawhar et al., Zero-padding techniques in OFDM systems, Int. J. Electr. Eng. Inform. 10 (2018), 704-725. https://doi.org/10.15676/ijeei.2018.10.4.6
  27. A. Hammoodi, L. Audah, and M. A. Taher, Green coexistence for 5G waveform candidates: A review, IEEE Access 7 (2019), 10103-10126. https://doi.org/10.1109/access.2019.2891312
  28. D. Wu et al., A field trial of f-OFDM toward 5G, in Proc. IEEE Globecom Workshops (Washington, DC, USA), Dec. 2016, pp. 1-6.
  29. R. Gerzaguet et al., The 5G candidate waveform race: A comparison of complexity and performance, EURASIP J. Wirel. Commun. Netw. 13 (2017), 1-14.
  30. J. Wang et al., Spectral efficiency improvement with 5G technologies: Results from field tests, IEEE J. Sel. Area. Commun. 35 (2017), 1867-1875. https://doi.org/10.1109/JSAC.2017.2713498
  31. D. Wu et al., A field trial of f-OFDM toward 5G, in Proc. Globecom Workshops (Washington, DC, USA), Dec. 2016, pp. 1-6.
  32. Y. Jawhar et al., New low complexity segmentation scheme of partial transmit sequence technique to reduce the high PAPR value in OFDM systems, ETRI J. 40 (2018), 1-15. https://doi.org/10.4218/etr2.12019
  33. F. Schaich and T. Wild, Waveform contenders for 5G-OFDM vs. FBMC vs. UFMC, in Proc. Commun., Contr. Signal Process. (Athens, Greece), May 2014, pp. 457-460.
  34. C. Berrou, A. Glavieux, and P. Thitimajshima, Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1, in Proc. ICC 93-IEEE Int. Conf. Commun. (Geneva, Switzerland), May 1993, pp. 1064-1070.
  35. B. Tahir, S. Schwarz, and M. Rupp, BER comparison between convolutional, turbo, LDPC, and polar codes, in Proc. Int. Conf. Telecommun. (Limassol, Cyprus), May 2017, pp. 1-7.
  36. E. Arikan, Channel polarization: A method for constructing capacity-achieving codes for symmetric binary-input memoryless channels, IEEE Trans. Inf. Theory 55 (2009), 3051-3073. https://doi.org/10.1109/TIT.2009.2021379
  37. Z. R. M. Hajiyat et al., Channel coding scheme for 5G mobile communication system for short length message transmission, Wirel. Pers. Commun. 106 (2019), 377-400. https://doi.org/10.1007/s11277-019-06167-7