Abstract
For underwater blue–green light multiple-input multiple-output orthogonal frequency division multiplexing modulation system (MIMO-OFDM), the underwater MIMO channel gain matrix corresponding to the change of receiver spacing was analyzed and derived, and a proportional power allocation scheme combined with singular value decomposition (SVD) precoding was proposed, in order to eliminate inter-channel interferences of the MIMO system. The simulation results show that when the transmitter spacing is fixed, and the receivers adopt the same spacing as the transmitters, which is difficult to achieve in the complex underwater environment, the system bit error rate (BER) performance under the proposed proportional power allocation scheme is the same as that of the average power allocation. When the receiver spacing increases, the system BER under the proposed scheme can ensure better overall performance compared with that of the traditional average allocation scheme.
Funding source: Xi’an University of Posts and Telecommunications Joint Postgraduate Cultivation Workstation
Award Identifier / Grant number: YJGJ201905
Funding source: Innovation Capability Support Program of Shaanxi
Award Identifier / Grant number: 2021TD-09
Funding source: Shaanxi Province Scientific and Technological Innovation Guidance Special Project
Award Identifier / Grant number: 2020TG-001
Funding source: Key Research and Development Program of Shaanxi
Award Identifier / Grant number: 2019KW-052
Acknowledgments
The authors would like to thank every anonymous reviewer for his/her detailed comments and the support of the following projects: Innovation Capability Support Program of Shaanxi (Program No. 2021TD-09). Key Research and Development Program of Shaanxi (Program No. 2019KW-052). Shaanxi Province Scientific and Technological Innovation Guidance Special Project (Program No. 2020TG-001). Xi’an University of Posts and Telecommunications Joint Postgraduate Cultivation Workstation (YJGJ201905).
-
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
-
Research funding: None declared.
-
Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
1. Deng, C, Song, R, Li, X, Long, Z, Tan, B. Underwater MIMO short distance visible light communication based on CMOS camera. Opt Commun 2020;44:1–5.Search in Google Scholar
2. Song, Y. Underwater wireless visible light communication system based on MIMO-OFDM. Hangzhou: Zhejiang University; 2017.Search in Google Scholar
3. Stavn, RH, Weidemann, AD. Optical modeling of clear ocean light fields: Raman scattering effects. Appl Opt 1988;27:4002–11. https://doi.org/10.1364/ao.27.004002.Search in Google Scholar
4. Jamali, MV and Salehi, JA. On the BER of multiple-input multiple-output underwater wireless optical communication systems. In: 4th International Workshop on Optical Wireless Communications (IWOW); 2015:26–30 pp.10.1109/IWOW.2015.7342259Search in Google Scholar
5. Xu, J, Kong, M, Lin, A, Song, Y, Yu, X, Qu, F, et al.. OFDM-based broadband underwater wireless optical communication system using a compact blue LED. Opt Commun 2016;369:100–5. https://doi.org/10.1016/j.optcom.2016.02.044.Search in Google Scholar
6. Cheng, H. Research on channel correlation and inter channel interference of indoor MIMO visible light communication system. Nanjing: Nanjing University of Posts and Telecommunications; 2020.Search in Google Scholar
7. Narieda, S, Yamashita, K. Optimal linear precoding with the extreme bounds of eigenmode SNR variation. IEEJ Trans. Electron. Inf. Syst. 2005;125:1422–9. https://doi.org/10.1541/ieejeiss.125.1422.Search in Google Scholar
8. Wang, H, Sun, Z. Indoor MIMO VLC system based on substreams selected BD precoding algorithm. Optoelectron Technol 2015;35:126–30.Search in Google Scholar
9. Fath, T, Hass, H. Performance comparison of MIMO techniques for optical wireless communications in indoor environments. IEEE Trans Commun 2013;61:733–42. https://doi.org/10.1109/tcomm.2012.120512.110578.Search in Google Scholar
10. Zhang, H, Zhu, Y. MIMO decorrelation for visible light communication based on angle optimization. Adv Mater Machinery Electron 2017;2017:1–5. https://doi.org/10.1063/1.4977399.Search in Google Scholar
11. Li, Y, Geng, T, Tian, R, Gao, S. Power allocation in a spatial multiplexing free-space optical system with reinforcement learning. Opt Commun 2021;488:126856. https://doi.org/10.1016/j.optcom.2021.126856.Search in Google Scholar
12. Zeng, Y, Wang, J, Ling, X, Liang, X, Zhao, C. Joint precoder and DC bias design for MIMO VLC systems. In: 17th International Conference on Communication Technology (ICCT); 2017:1180–5 pp.10.1109/ICCT.2017.8359821Search in Google Scholar
13. Zhao, R, Fu, J, Li, Y, Lin, J. Power optimization of underwater blue and green light imaging MIMO system based on DCO-OFDM. Opt. Fiber Technol 2019;43:41–6.Search in Google Scholar
14. Wang, P, Li, C, Xu, Z. A cost-efficient real-time 25 Mb/s system for LED-UOWC: design, channel coding, FPGA implementation, and characterization. J Lightwave Technol 2018;36:2627–37. https://doi.org/10.1109/jlt.2018.2819985.Search in Google Scholar
15. Yang, Y, He, F, Guo, Q, Wang, M, Duan, Z. Analysis of underwater wireless optical communication system performance. Appl Opt 2019;58:9808–14. https://doi.org/10.1364/ao.58.009808.Search in Google Scholar PubMed
16. Kerker, M. Physical optics of ocean water. J Colloid Interface Sci 1988;126:386. https://doi.org/10.1016/0021-9797(88)90136-1.Search in Google Scholar
17. Cox, W, Muth, J. Simulating channel losses in an underwater optical communication system. J Opt Soc Am A 2014;31:920–34. https://doi.org/10.1364/josaa.31.000920.Search in Google Scholar
18. Carruthers, JB, Kahn, JM. Modeling of nondirected wireless infrared channels. IEEE Trans Commun 1997;45:1260–8. https://doi.org/10.1109/26.634690.Search in Google Scholar
19. Yang, B, Zhao, L, Liu, Y, Zhao, Y. Research on MIMO channel capacity for adaptive power allocation visible light. J Appl Opt 2020;41:626–30.10.5768/JAO202041.0308002Search in Google Scholar
20. Guerreiro, J, Rui, D, Campos, L. On the achievable capacity of MIMO-OFDM systems in the CathLab environment. Sensors 2020;20:938. https://doi.org/10.3390/s20030938.Search in Google Scholar PubMed PubMed Central
© 2022 Walter de Gruyter GmbH, Berlin/Boston