Analytical performance evaluation of GFDM in underwater acoustic communication systems
Keywords:Probability theory, GFDM, performance appraisal, telecommunications, underwater technology
The rapid growth of the Internet of Things (IoT) has extended its concept to underwater environments. However, the implementation of these systems via wired communication still represents a technological challenge, mainly due to the high cost of their deployment. Therefore, wireless communications are seen as an interesting solution for the deployment of underwater communications systems. Preliminary research indicated that underwater acoustic wireless communication could be used for some Internet of Underwater Things applications, mainly due to the wide range of communications involved. However, a significant disadvantage of acoustic systems is their low transmission data rate; thus, studies and analyses to improve this disadvantage must be carried out. Considering that new waveforms have been proposed to improve the performance of terrestrial wireless communications systems, this work presents the development of general analytical expressions that allow the performance evaluation of the Generalized Frequency Division Multiplexing (GFDM) waveform in underwater environments. These analytical expressions were obtained considering a continuous-time model for the GFDM signal and modeling the underwater acoustic communication channel as a time-varying multipath channel. Numerical results were obtained for many different systems and channel parameters, allowing a quantitative evaluation of the system performance degradation.
C. Kao and et al, “A study of applications, challenges, and channelmodels on the internet of underwater things,” in IEEE InternationalConference on Applied System Innovation (ICASI), Sapporo, Japan,2017, pp. 1375–1378. [Online]. Available: https://doi.org/10.1109/ICASI.2017.7988162
E. Liou and et al, “Internet of underwater things: Challengesand routing protocols,” in IEEE International Conference on AppliedSystem Invention (ICASI), Chiba, Japan, 2018, pp. 1171–1174.[Online]. Available: https://doi.org/10.1109/ICASI.2018.8394494
S. Premkumardeepak and M. Mukesh, “Intelligent sensor basedmonitoring system for underwater pollution,” in InternationalConference on IoT and Application (ICIOT), Nagapattinam, India, 2017,pp. 1–4. [Online]. Available: https://doi.org/10.1109/ICIOTA.2017.8073626
C. Chiang, “A CMOS seawater salinity to digital converter for IoTapplications of fish farms,” IEEE Transactions on Circuits and SystemsI: Regular Papers, vol. 64, no. 9, pp. 2591–2597, 2017. [Online].Available: https://doi.org/10.1109/TCSI.2017.2686582
C. A. Perez and et al, “Design and deployment of a wireless sensornetwork for the mar menor coastal observation system,” IEEEJournal of Oceanic Engineering, vol. 42, no. 4, pp. 966–976, 2017.[Online]. Available: https://doi.org/10.1109/JOE.2016.2639118
E. Fischell, T. Schneider, and H. Schmidt, “Design, implementation,and characterization of precision timing for bistatic acoustic dataacquisition,” IEEE Journal of Oceanic Engineering, vol. 41, no. 3,pp. 583–591, 2016. [Online]. Available: https://doi.org/10.1109/JOE.2015.2469975
S. M. Maher and et al, “Performance of rf underwatercommunications operating at 433 mhz and 2.4 GHz,” inInternational Conference on Innovative Trends in ComputerEngineering, Egypt, Egypt, 2019, pp. 334–339. [Online]. Available: https://doi.org/10.1109/ITCE.2019.8646491
M. Jouhari and et al, “Underwater wireless sensor networks: Asurvey on enabling technologies, localization protocols, and internetof underwater things,” IEEE Access, vol. 7, pp. 96 879–96 899, 2019.[Online]. Available: https://doi.org/10.1109/ACCESS.2019.2928876
Z. Zeng and et al, “A survey of underwater optical wireless communications,” IEEE Commun. Surveys Tuts., vol. 19, no. 1, pp. 204–238, 2017. [Online]. Available: https://doi.org/10.1109/COMST.2016.2618841
H. Kaushal and G. Kaddoum, “Underwater optical wirelesscommunication,” IEEE Access, vol. 4, pp. 1518 – 1547, 2016.[Online]. Available: https://doi.org/10.1109/ACCESS.2016.2552538
S. Sendra and et al, “Underwater acoustic modems,” IEEE SensorsJournal, vol. 16, no. 11, pp. 4063–4071, 2016. [Online]. Available:https://doi.org/10.1109/JSEN.2015.2434890
H. S. Dol and et al, “Software-defined underwater acoustic modems:Historical review and the NILUS approach,” IEEE Journal of OceanicEngineering, vol. 42, no. 3, pp. 722–737, 2017. [Online]. Available: https://doi.org/10.1109/JOE.2016.2598412
S. Zhang and et al, “The localization algorithm based on symmetrycorrection for underwater acoustic networks,” IEEE Access, vol. 7,pp. 121 127–121 135, 2019. [Online]. Available: https://doi.org/10.1109/ACCESS.2019.2937106
D. Wang and et al, “Channel-adaptive location-assisted wake-upsignal detection approach based on LFM over underwater acousticchannels,” IEEE Access, vol. 7, pp. 93 806–93 819, 2019. [Online].Available: https://doi.org/10.1109/ACCESS.2019.2926531
Y. Zhou and F. Tong, “Channel estimation basedequalizer for underwater acoustic multiple-input-multiple-outputcommunication,” IEEE Access, vol. 7, pp. 79 005–79 016, 2019.[Online]. Available: https://doi.org/10.1109/ACCESS.2019.2921596
J. Zhou and et al, “Study of propagation channel characteristics forunderwater acoustic communication environments,” IEEE Access,vol. 7, pp. 79 438–79 445, 2019. [Online]. Available: https://doi.org/10.1109/ACCESS.2019.2921808
G. Qiao and et al, “Analysis of snr metrics for a typical underwateracoustic OFDM system,” IEEE Access, vol. 7, pp. 183 565–183 579,2019. [Online]. Available: https://doi.org/10.1109/ACCESS.2019.2960304
J. Li and et al, “Performance analysis for focused beamformers inpassive underwater acoustic localization,” IEEE Access, vol. 6, pp.18 200–18 208, 2018. [Online]. Available: https://doi.org/10.1109/ACCESS.2018.2821766
E. Demirors and et al, “A high-rate software-defined underwateracoustic modem with real-time adaptation capabilities,” IEEEAccess, vol. 6, pp. 18 602–18 615, 2018. [Online]. Available: https://doi.org/10.1109/ACCESS.2018.2815026
Y. Zhou and F. Tong, “Research and development of ahighly reconfigurable OFDM MODEM for shallow water acousticcommunication,” IEEE Access, vol. 7, pp. 123 569–123 582, 2019.[Online]. Available: https://doi.org/10.1109/ACCESS.2019.2936933
R. Jiang and et al, “Deep neural networks for channel estimationin underwater acoustic OFDM systems,” IEEE Access, vol. 7, pp.23 579–23 594, 2019. [Online]. Available: https://doi.org/10.1109/ACCESS.2019.2899990
J. Tao, “DFT-precoded MIMO OFDM underwater acousticcommunications,” IEEE Journal of Oceanic Engineering, vol. 43,no. 3, pp. 805–819, 2018. [Online]. Available: https://doi.org/10.1109/JOE.2017.2735590
I. de Almeida and et al, “5G waveforms for IoT applications,”IEEE Communications Surveys & Tutorials, vol. 21, no. 3, pp.2554–25 679, 2019. [Online]. Available: https://doi.org/10.1109/COMST.2019.2910817
Y. Tao and et al, “A survey: Several technologies of non-orthogonaltransmission for 5G,” China Communications, vol. 12, no. 10, pp. 1–15,2019. [Online]. Available: https://doi.org/10.1109/CC.2015.7315054
R. Gerzaguet and et al, “The 5G candidate waveform race: acomparison of complexity and performance,” Journal on WirelessCommunications and Networking, vol. 13, pp. 1–14, 2017. [Online].Available: https://doi.org/10.1186/s13638-016-0792-0
G. Fettweis, M. Krondorf, and S. Bittner, “GFDM - generalizedfrequency division multiplexing,” in IEEE 69th Vehicular TechnologyConference, Barcelona, Spain, 2009, pp. 1–4. [Online]. Available: https://doi.org/10.1109/VETECS.2009.5073571
Z. Na and et al, “Turbo receiver channel estimation for GFDM-Basedcognitive radio networks,” IEEE Access, vol. 6, pp. 9926–9935, 2018.[Online]. Available: https://doi.org/10.1109/ACCESS.2018.2803742
J. Zhong and et al, “Iterative frequency domain equalization forMIMO-GFDM systems,” IEEE Access, vol. 6, pp. 19 386–19 395, 2018.[Online]. Available: https://doi.org/10.1109/ACCESS.2018.2823002
H. Wang and R. Song, “Low complexity ZF receiver design formulti-user GFDMA uplink systems,” IEEE Access, vol. 6, pp.28 661–28 667, 2018. [Online]. Available: https://doi.org/10.1109/ACCESS.2018.2839750
P. Chen, B. Su, and Y. Huang, “Matrix characterization for GFDM: Lowcomplexity MMSE receivers and optimal filters,” IEEE Transactionson Signal Processing, vol. 65, no. 18, pp. 4940–4955, 2017. [Online].Available: https://doi.org/10.1109/TSP.2017.2718971
S. Tiwari and S. S. Das, “Low-complexity joint-MMSE GFDMreceiver,” IEEE Transactions on Communications, vol. 66, no. 4,pp. 1661–1674, 2017. [Online]. Available: https://doi.org/10.1109/TCOMM.2017.2780854
A. Hilario-Tacuri and et al, “Performance evaluation of generalizedfrequency division multiplexing systems over non-linearities withmemory,” IEEE Access, vol. 7, pp. 119 131–119 139, 2019. [Online].Available: https://doi.org/10.1109/ACCESS.2019.2936840
Z. Wang, L. Mei, X. Sha, and V. Leung, “BER analysis of WFRFTprecoded OFDM and GFDM waveforms with an integer time offset,”IEEE Transactions on Vehicular Technology, vol. 67, no. 10, pp.9097–9111, 2018. [Online]. Available: https://doi.org/10.1109/TVT.2018.2855696
Z. Wang, L. Mei, and X. Sha, “BER analysis for GFDM systems withgabor MMSE receiver,” IEEE Communications Letters, vol. 22, no. 11,pp. 2222–2225, 2018. [Online]. Available: https://doi.org/10.1109/LCOMM.2018.2868107
A. Hilario-Tacuri, “A closed-form spectral analysis of GFDM in underwater communication systems,” in 2019 IEEE Latin-AmericanConference on Communications (LATINCOM), Salvador, Brazil,2019, pp. 1–6. [Online]. Available: https://doi.org/10.1109/LATINCOM48065.2019.8937919
M. J. Bocus, A. Doufexi, and D. Agrafiotis, “Performance evaluationof filterbank multicarrier systems in an underwater acousticchannel,” in 27th Annual IEEE International Symposium on Personal,Indoor and Mobile Radio Communications, Valencia, Spain, 2016,pp. 1–6. [Online]. Available: https://doi.org/10.1109/PIMRC.2016.7794717
Y. Liu and et al, “Performance analysis of OFDM over multi-scalemulti-lag channels,” in IEEE 86th Vehicular Technology Conference(VTC-Fall), Toronto, Canada, 2017, pp. 1–5. [Online]. Available: https://doi.org/10.1109/VTCFall.2017.8287943
M. J. Bocus, A. Doufexi, and D. Agrafiotis, “Non-orthogonal multipleaccess (NOMA) for underwater acoustic communication,” in IEEE86th Vehicular Technology Conference (VTC-Fall), Chicago, USA, 2018,pp. 1–5. [Online]. Available: https://doi.org/10.1109/VTCFall.2018.8690996
J. Proakis and M. Salehi, Digital Communications, 5th ed. New York,USA: McGraw-Hill, 2008.
M. Pätzold, Mobile fading channels, 1st ed. New York, USA: JohnWiley & Sons, 2002.
How to Cite
Copyright (c) 2021 Revista Facultad de Ingeniería Universidad de Antioquia
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Revista Facultad de Ingeniería, Universidad de Antioquia is licensed under the Creative Commons Attribution BY-NC-SA 4.0 license. https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en
You are free to:
Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material
Under the following terms:
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
The material published in the journal can be distributed, copied and exhibited by third parties if the respective credits are given to the journal. No commercial benefit can be obtained and derivative works must be under the same license terms as the original work.