Transmit Beamforming for Underwater Acoustic OFDM Systems

被引:4
|
作者
Cuji, Diego A. [1 ]
Stojanovic, Milica [2 ]
机构
[1] Northeastern Univ, Elect Engn, Boston, MA 02115 USA
[2] Northeastern Univ, Boston, MA 02115 USA
关键词
Acoustic feedback; channel estimation; differentially coherent detection; null-steering; orthogonal frequency division multi-plexing (OFDM); path-identification; transmit beamforming; underwater acoustic communications; PERFORMANCE ANALYSIS; DESIGN;
D O I
10.1109/JOE.2023.3295474
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This article addresses the problem of transmit beamforming for underwater acoustic communication systems within the framework of multicarrier signaling based on orthogonal frequency division multiplexing (OFDM). The system consists of a transmitter equipped with a uniform linear array and a single receiver. Transmit beamforming requires the transmitter to have complete knowledge of the channel to the receiver; however, this assumption is often not justified in acoustic channels with long feedback delays. To counteract this problem, we propose a technique that targets only those features of the channel that can withstand the feedback delay. One such feature is the angle of arrival of the principal propagation path, which does not experience rapid variations caused by surface scattering, and is thus, varying sufficiently slowly that it can tolerate long feedback delays. OFDM provides an ideal platform for implementing broadband beamforming, and we study the system performance in terms of the data detection mean squared error (MSE) and bit error rate (BER), using synthetic data transmitted over a 1 km shallow water channel in the 10-15 kHz acoustic band. Specifically, we show that beamforming in the principal path's direction achieves excellent MSE performance, with only a few dB degradation with respect to optimal beamforming. We present results for different receive-side detection methods, namely, differentially coherent detection and coherent detection. In addition, we propose an angle tracking algorithm to reduce the complexity in mobile systems, and we demonstrate the system performance using an over-the-air acoustic communications testbed.
引用
收藏
页码:145 / 162
页数:18
相关论文
共 50 条
  • [1] Channel Estimation Based on Adaptive Denoising for Underwater Acoustic OFDM Systems
    Cho, Yong-Ho
    Ko, Hak-Lim
    IEEE ACCESS, 2020, 8 (08): : 157197 - 157210
  • [2] Successive transmit beamforming algorithms for multiple-antenna OFDM systems
    Liu, Li
    Jafarkhani, Hamid
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2007, 6 (04) : 1512 - 1522
  • [3] Capacity of OFDM Systems Over Fading Underwater Acoustic Channels
    Polprasert, Chantri
    Ritcey, James A.
    Stojanovic, Milica
    IEEE JOURNAL OF OCEANIC ENGINEERING, 2011, 36 (04) : 514 - 524
  • [4] Impact of Transceiver I/Q Imbalance on Transmit Diversity of Beamforming OFDM Systems
    Maham, Behrouz
    Tirkkonen, Olav
    Hjorungnes, Are
    IEEE TRANSACTIONS ON COMMUNICATIONS, 2012, 60 (03) : 643 - 648
  • [5] Fast Sparse Bayesian Learning-Based Channel Estimation for Underwater Acoustic OFDM Systems
    Cho, Yong-Ho
    APPLIED SCIENCES-BASEL, 2022, 12 (19):
  • [6] Impulsive Noise Mitigation in Underwater Acoustic OFDM Systems
    Kuai, Xiaoyan
    Sun, Haixin
    Zhou, Shengli
    Cheng, En
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2016, 65 (10) : 8190 - 8202
  • [7] Synchronization, Doppler and channel estimation for OFDM underwater acoustic communications
    Trubuil, Joel
    Le Gall, Thierry
    Chonavel, Thierry
    OCEANS 2014 - TAIPEI, 2014,
  • [8] Distributed compressed sensing estimation of underwater acoustic OFDM channel
    Zhou, Yue-hai
    Tong, F.
    Zhang, Gang-qiang
    APPLIED ACOUSTICS, 2017, 117 : 160 - 166
  • [9] Cross power spectral density based beamforming for underwater acoustic communications
    Li, Jianghui
    Bai, Yechao
    Zhang, Youwen
    Qu, Fengzhong
    Wei, Yan
    Wang, Junfeng
    OCEAN ENGINEERING, 2020, 216
  • [10] Superposition Coding for Downlink Underwater Acoustic OFDM
    Ma, Lu
    Zhou, Shengli
    Qiao, Gang
    Liu, Songzuo
    Zhou, Feng
    IEEE JOURNAL OF OCEANIC ENGINEERING, 2017, 42 (01) : 175 - 187