A Novel Non-Stationary Geometry-Based Stochastic Model for Underwater Acoustic MIMO Communication Systems in Shallow Seas

Ma, Yilin; Wang, Cheng-Xiang; Chang, Hengtai; Huang, Jie; Wang, Jun; An, Liang; Chen, Yunfei

Abstract

Underwater acoustic (UWA) channel models are indispensable for the design of UWA communication systems and technologies. In this paper, a novel non-stationary three-dimensional (3D) twin cluster geometry-based stochastic model (GBSM) is proposed for multiple-input multiple-output (MIMO) UWA communication systems in shallow seas. The distribution of non-line-of-sight (NLoS) delays obeys the Nakagami distribution in this model according to the results generated by Bellhop. In addition, the relationship between delay and power is modeled as a negative exponential distribution with different parameters for each NLoS component. The periodic mobility of clusters and distribution of scatterers, caused by the fluctuations of sea surface, are considered to account for the unique UWA environment. Channel statistical properties, such as the space-time-frequency correlation function (STFCF), Doppler power spectrum density (PSD), Doppler spread, coherence time, and coherence distance, are investigated. In particular, temporal autocorrelation function (TACF) and frequency correlation function (FCF) are compared with measurement data to validate the accuracy of this model. Simulation results show that the fluctuating sea surface can cause significant changes in UWA channel characteristics, making it indispensable in channel modeling.

Citation

Ma, Y., Wang, C.-X., Chang, H., Huang, J., Wang, J., An, L., & Chen, Y. (online). A Novel Non-Stationary Geometry-Based Stochastic Model for Underwater Acoustic MIMO Communication Systems in Shallow Seas. IEEE Internet of Things Journal, https://doi.org/10.1109/JIOT.2025.3591731

• Journal Article Type: Article
• Acceptance Date: Jul 11, 2025
• Online Publication Date: Jul 22, 2025
• Deposit Date: Jul 16, 2025
• Publicly Available Date: Jul 25, 2025
• Journal: IEEE Internet of Things Journal
• Electronic ISSN: 2327-4662
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1109/JIOT.2025.3591731
• Public URL: https://durham-repository.worktribe.com/output/4268295
• Publisher URL: https://ieeexplore.ieee.org/xpl/aboutJournal.jsp?punumber=6488907