带内全双工水声通信凭借其高频谱利用率的优势，已成为应对水下可用通信带宽有限这一现实问题的重要技术方案。然而，其自身辐射信号会对远端水声通信信号的接收产生显著干扰。通过利用已知的自干扰信号副本，并采用自适应滤波算法在数字域进行自干扰抵消，是实现带内全双工水声通信的关键所在。为兼顾自干扰中的线性分量和非线性分量抵消，本文基于模拟辅助的数字域自干扰抵消结构给出系统模型，结合通信误码率从稳态误差、收敛速度和计算量等方面对比研究了LMS算法、AP算法和RLS算法应用于带内全双工水声通信数字域自干扰抵消的性能，重点分析了辅助支路量化位数和接收信号信干比不同时的自干扰抵消效果。仿真结果表明，3种算法各有优势，但AP算法可以以适中的计算量、收敛速度和稳态误差完成接收信号不同信干比和辅助支路存在噪声条件下的自干扰抵消，辅助支路量化位数8位、接收信号信干比为–30 dB时可达到0.01的通信误码率。
In-band full-duplex underwater acoustic communication (IBFD-UWAC), with its advantage of high spectral utilization rate, has become an important technical solution to deal with the practical problem of limited available bandwidth underwater. However, the signal emitted by itself can cause significant interference to the reception of underwater acoustic communication signals at the remote end. Using known replicas of self-interference signals and applying an adaptive filtering algorithm for self-interference cancellation in the digital domain is crucial for enabling in-band full-duplex underwater acoustic communication. To achieve a balance in the cancellation of both linear and nonlinear components of self-interference, this paper proposes a system model based on an analog-assisted digital domain self-interference cancellation structure. In conjunction with the communication bit error rate, the performance of the LMS algorithm, AP algorithm, and RLS algorithm applied to self-interference cancellation is comparatively analyzed in terms of steady-state error, convergence speed, and computational complexity. Additionally, the self-interference cancellation performance of the auxiliary branch is thoroughly investigated under varying conditions of quantization bit numbers and signal-to-interference ratios of the received signals. The simulation results demonstrate that each of the three algorithms possesses distinct advantages. Nevertheless, the AP algorithm is capable of achieving self-interference cancellation under varying signal-to-interference ratios of the received signal and noise in the auxiliary branch. This is accomplished with moderate computational complexity, convergence rate, and steady-state error. Specifically, when the quantization bit of the auxiliary branch is set to 8 bits and the signal-to-interference ratio of the received signal is -30 dB, a communication bit error rate of 0.01 can be attained.
2026,48(5): 115-121 收稿日期：2025-6-18
DOI：10.3404/j.issn.1672-7649.2026.05.018
分类号：U66；TN929.3
作者简介：曹洪茹(1995-),女,博士生,研究方向为水声通信及信号处理
参考文献：
[1] SHEN L, HENSON B, ZAKHAROV Y, et al. Digital self-interference cancellation for full-duplex underwater acoustic systems[J]. IEEE Transactions on Circuits and Systems II: Express Briefs, 2019, 67(1): 192-196
[2] LU Y H, GANG Q, YANG C L, et al. A real-time digital self-interference cancellation method for in-band full-duplex underwater acoustic communication based on improved VSS-LMS algorithm[J]. Remote Sensing 14, no. 12: 2924.
[3] 赵云江. 带内全双工水声通信自干扰抵消关键技术研究[D]. 哈尔滨: 哈尔滨工程大学, 2021.
[4] QIAO G, LU Y, LOU Y, et al. Research on real-time simulated self-interference cancellation technology of full duplex underwater acoustic communication[C]//Proceedings of 2021 OES China Ocean Acoustics (COA), Harbin, China, 2021.
[5] 董佳鑫. MIMO同时收发系统的自干扰消除技术研究[D]. 西安: 西安电子科技大学, 2023.
[6] 赵云江, 张小华. 基于残余自干扰获取的带内全双工水声通信系统结构方案与仿真[J]. 数字海洋与水下攻防, 2022, 5(5): 387-396
ZHAO Y J, ZHANG X H. In-band full-duplex underwater acoustic communication system structural scheme and simulation based on residual self-interference acquisition[J]. Digital Ocean & Underwater Warfare, 2022, 5(5): 387-396
[7] LEI D, ZHOU G T, MORGAN D R, et al. A robust digital baseband predistorter constructed using memory polynomials[J]. IEEE Trans. Commun. , 2004, 52(1): 159–165.
[8] Simon Haykin著, 郑宝玉, 等译. 自适应滤波器原理(第四版)[M]. 北京: 电子工业出版社, 2003.
[9] 夏晓. 自适应滤波器中LMS算法的研究及应用[D]. 北京: 北京邮电大学, 2013.
[10] 黄兴利, 慕德俊, 肖磊, 等. 仿射投影算法收敛特性随机统计特性的研究[J]. 西北工业大学学报, 2015, 33(3): 484-488
HUANG X L, MU D J, XIAO L, et al. A statistical analysis of convergence of affine projection algorithm[J]. Journal of Northwestern Polytechnical University, 2015, 33(3): 484-488
[11] CASTOLDI F T, CAMPOS M L R. Application of a minimum-disturbance description to constrained adaptive filters[J]. IEEE Signal Processing Letters, 2013, 20(12): 1215-1218
[12] 师黎明. 仿射投影类自适应滤波算法的改进算法研究[D]. 重庆: 重庆邮电大学, 2015.
[13] 王少丹. 收发同时DRFM干扰机中自干扰对消技术的研究[D]. 哈尔滨: 哈尔滨工程大学, 2020.
[14] 鲁人杰. 干扰机的数字域自干扰对消技术研究[D]. 哈尔滨: 哈尔滨工程大学, 2023.
[15] 刘建成, 赵宏志, 全厚德, 等. 迭代变步长LMS算法及性能分析[J]. 电子与信息学报, 2015, 37(7): 1674–1680.
LIU J C, ZHAO H Z, QUAN H D, et al. Iteration-based variable step-size LMS algorithm and its performance analysis[J]. Journal of Electronics & Information Technology, 2015, 37(7): 1674–1680.
[16] 张兰勇, 王民, 刘胜, 等. 一种新的变步长自适应噪声消除算法[J]. 电子学报, 2017, 45(2): 321-327
ZHANG L Y, WANG M, LIU S, et al. A novel variable step-size adaptive interference cancellation algorithm[J]. Acta Electronica Sinica, 2017, 45(2): 321-327
[17] 焦海泉. 基于仿射投影算法的自适应回声消除研究[D]. 天津: 天津大学, 2018.
[18] 杨晨璐. 声诱饵的空间数字域自干扰抵消技术研究[D]. 哈尔滨: 哈尔滨工程大学, 2023.
[19] 毛蓓. 收发同时系统中数字域干扰对消技术研究[D]. 哈尔滨: 哈尔滨工程大学, 2022.
[20] 晁鹏. 自适应滤波理论及其水声通信自干扰抵消应用研究[D]. 镇江: 江苏科技大学, 2023.
[21] 高世杰. 基于自适应滤波的水声通信干扰消除研究[D]. 镇江: 江苏科技大学, 2021.
[22] LU Y H, QING X, YANG C L, et al. Spatial-digital joint self-interference cancellation method for in-band full-duplex underwater acoustic communication[J]. Frontiers in Marine Science, 2022, 9.
