GUO Yin-jing1,2, LIU Zhen1, YANG Wen-jian1, NIU Chen-xi1, LIU Hui1
(1. College of Electronic Information Engineering, Shandong University of Science and Technology, Qingdao 266590, China;2. Qingdao Zhihai Muyang Technology Co., Ltd., Qingdao 266590, China)
Abstract: The complexity of underwater environment poses a challenge to underwater acoustic communication. In marine environment, different temperatures, depths and salinities would affect the performance of acoustic communication. The analysis of the underwater acoustic channel under the influence of temperature factors provides a reference for further study of the underwater acoustic channel estimation problem based on filter bank multi-carrier(FBMC). The FBMC based offset quadrature amplitude modulation(OQAM) technology(FBMC/OQAM) was introduced into the underwater acoustic communication. Based on FBMC, the underwater acoustic channel estimation technology was studied. By changing the pilot structure to adapt to the complex and variable underwater acoustic channel, the iterative method was used to obtain the channel information with higher accuracy and further improve the performance of channel estimation. Theoretical analysis and simulation results show that iterative channel estimation algorithm based on the new interference approximation method (IAM) pilot proposed in this paper has better performance in underwater acoustic channel.
Key words: filter bank multi-carrier (FBMC); underwater acoustic channel estimation; temperature; pilot; interference approximation method (IAM)
CLD number: TJ630.33; U675.7; U674.941 doi: 10.3969/j.issn.1674-8042.2020.02.013
References
[1]Schellmann M, Zhao Z, Lin H, et al. FBMC-based air interface for 5G mobile: challenges and proposed solution. In: Proceedings of 9th International Conference on Cognitive Radio Oriented Wireless Networks and Communications(CROWNCOM), IEEE, 2014: 102-107.
[2]Eiayoubi S E, Boldi M, Bulakci O, et al. Preliminary views and initial considerations on 5G RAN architecture and functional design. Project White Paper METIS II, 2016: 1-27.
[3]Viholainen A, Bellanger M, Huchard M. Phydas-physical layer for dynamic access and cognitive radio. Report, 2009, (5): 1.
[4]Du J, Signell S. Time frequency localization of pulse shaping filters in OFDM/OQAM systems. In: Proceedings of 6th International Conference on Information, Communications & Signal Processing, IEEE, 2007: 1-5.
[5]Gharba M, Legouable R, Siohan P. An alternative multiple access scheme for the uplink 3GPP/LTE based on OFDM/OQAM. In: Proceedings of 7th International Symposium on Wireless Communication Systems, IEEE, 2010: 941-945.
[6]Wang C L, Wang S C. A new preamble design for channel estimation in offset QAM filter bank multicarrier systems. In: Proceedings of IEEE Global Communications Conference (GLOBECOM), IEEE, 2018: 1-6.
[7]Lélé C, Legouable R, Siohan P. Channel estimation with scattered pilots in OFDM/OQAM. In: Proceedings of IEEE 9th Workshop on Signal Processing Advances in Wireless Communications, IEEE, 2008: 286-290.
[8]Ni S X. Research on PAPR suppression and channel estimation technology of FBMC system. Hangzhou: Zhejiang University, 2019.
[9]He Z M, Zhou L Y, Yang Y, et al. DFT-based channel estimation refinement by clustering in FBMC-OQAM system. The Journal of Engineering, 2019, (3): 652-656.
[10]Lélé C, Javaudin J, Legouable R, et al. Channel estimation methods for preamble-based OFDM/OQAM modulations. European Transactions on Telecommunications, 2010, 19(7): 741-750.
[11]Du J, Signell S. Novel preamble-based channel estimation for OFDM/OQAM systems. In: Proceedings of IEEE International Conference on Communications, IEEE, 2009, 7(9): 4135-4140.
[12]Kofidis E, Katselis D. Improved interference approximation method for preamble-based channel estimation in FBMC/OQAM. In: Proceedings of Signal Processing Conference, IEEE, 2011, 10(19): 1603-1607.
[13]Fuhrwerk M, Moghaddamnia S, Peissig J. Scattered pilot-based channel estimation for channel adaptive FBMC-OQAM systems. IEEE Transactions on Wireless Communications, 2017, 16(3): 1687-1702.
[14]Domingo M C. Overview of channel models for underwater wireless communication networks. Physical Communication, 2008, 1(3): 163-182.
[15]Liu G H, Li P. IAM preamble channel estimation algorithm based on iterative FBMC/OQAM system. Computer Measurement and Control, 2018, (10): 40.
[16]Geoffroy M, Daase M, Cusa M, et al. Mesopelagic sound scattering layers of the high arctic: seasonal variations in biomass, species assemblage, and trophic relationships. Frontiers in Marine Science, 2019, 6: 1-18.
[17]Kyhn L A, Waisniewska D M, Beedholm K, et al. Basin-wide contributions to the underwater soundscape by multiple seismic surveys with implications for marine mammals in Baffin Bay, Greenland. Marine Pollution Bulletin, 2019, 138: 474-490.
[18]Cottet E, Murphy P, Bassett C, et al. Acoustic characterization of sensors used for marine environmental monitoring. Marine Pollution Bulletin, 2019, 144: 205-215.
[19]Hildebrand J A, Frasier K E, Banmann P S, et al. Assessing seasonality and density from passive acoustic monitoring of signals presumed to be from pygmy and dwarf sperm whales in the Gulf of Mexico. Frontiers in Marine Science, 2019, 6: 66.
基于FBMC的水声信道估计与温度因素的研究
郭银景1,2, 刘 珍1, 杨文健1, 牛晨曦1, 刘 辉1
(1. 山东科技大学 电子信息工程学院, 山东 青岛 266590;2. 青岛智海牧洋科技有限公司, 山东 青岛 266590)
摘 要: 水下环境的复杂性对水声通信带来挑战, 不同温度、 深度和盐度的海洋环境对通信性能的影响值得关注。 本文对温度因素影响下的水声信道进行分析, 为进一步研究基于滤波器组多载波(FBMC)水声信道估计问题提供了参考。 将FBMC/OQAM调制技术引入水下, 研究基于FBMC的水声信道估计技术。 通过改进导频结构来适应复杂多变的水声信道, 采用迭代方法获得精确度更高的信道信息, 进一步提高信道估计性能。 理论分析和仿真结果表明, 本中所提的新基于干扰近似方法(IAM)导频迭代信道估计算法在水声信道中有更好的性能。
关键词: 滤波器组多载波(FBMC); 水声信道估计; 温度; 导频; 干扰近似方法(IAM)
引用格式: GUO Yin-jing, LIU Zhen, YANG Wen-jian, et al. Research on underwater acoustic channel estimation and temperature factors based on FBMC. Journal of Measurement Science and Instrumentation, 2020, 11(2): 197-204. [doi: 10.3969/j.issn.1674-8042.2020.02.013]
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