Long-range underwater acoustic communication (LR-UWAC) is an essential technique for applications such as the control of unmanned underwater vehicles, gliders, or tactical submarines for long-term monitoring tasks. While techniques for estimating the channel impulse response (CIR) of short-range UWAC have been successfully applied, this is not the case for LR-UWAC. Here, the main challenge is to handle the diverse channel structure, which can be of a sparse or a non-sparse structure. In this paper, we propose a robust channel estimator for LR-UWAC. Our solution includes a switching mechanism to classify the channel as either sparse or non-sparse. In its sparse form, the LR-UWAC channel is characterized by a long time delay spread, time-invariant characteristics, and a block structure. Thus, we propose a non-trivial combination of the block subspace pursuit and the distributed subspace pursuit algorithms to exploit the channel’s block structure. For non-sparse LR-UWAC channel structures, we approximate the received signal as Gaussian, and derive a maximum-likelihood (ML) estimator to separate the non-resolvable multipath. Extensive numerical simulation and results from two long-range sea experiments demonstrate the efficiency of our approach in identifying the channel’s structure, and to accurately estimate the channel compared to state-of-the-art benchmarks.

While underwater acoustic (UWA) communication offers a practical way to establish a wireless link with underwater vehicles, designing a UWA communication system onboard a small autonomous underwater vehicle (AUV) still poses significant challenges. As the adoption of the low-complexity, robust noncoherent communication technology is limited by low bandwidth efficiency and a low data rate, coherent UWA communication requires Doppler mitigation and channel equalization measures to achieve a relatively high data rate in a moving state. Due to the strict constraints of a small-scale AUV in terms of resources and energy consumption, it is not appropriate to use high-complexity Doppler/multipath compensation technology from the prospect of system implementation. In this paper, an efficient and low-complexity UWA differential binary phase-shift keying (DBPSK) system onboard a small AUV is proposed by simplifying the Doppler and multipath compensation. Specifically, for Doppler, the delay of the adjacent DBPSK symbols is calculated according to the Doppler estimate to facilitate delay-tuning Doppler correction. For multipath, low-complexity LMS channel equalization is incorporated with error correction coding to enable multipath mitigation. With a simple structure and low computational complexity, the proposed scheme facilitates the practical hardware implementation and system integration in the small AUV platform. The numerical simulations are conducted to assess the validity of the proposed scheme under different channel conditions and the effectiveness of the proposed scheme is further verified by two UWA communication field tests, which are performed at a practical shallow water sea and lake, respectively.

Due to the combined effects of different acoustic propagation, reflection patterns in different time-scale, time-varying underwater acoustic (UWA) channel generally exhibits hybrid sparsity, i.e., contains not only rapidly time-varying elements, but also stationary or slowly time-varying ones. While the classic sparse reconstruction algorithms such as orthogonal matching pursuit (OMP) generally do not take it into account, the existence of static multipath will unavoidably hinder the tracking of rapid time variations. In this paper, a sequential adaptive observation length orthogonal matching pursuit (SAOLOMP) approach is proposed to sequentially explore rapidly time-varying sparsity in a two-step sequential manner. Specifically, the static components are firstly separated via simultaneous orthogonal matching pursuit (SOMP) among continuous measurements. Upon the residual error of the SOMP, the measurement-wise OMP is applied for estimating the remained dynamic components. As the variation of the SOMP residual error indicates how rapidly the remained dynamic multipath components vary, the observation length of the OMP is adjusted according to the gradient of residual error to adapt to rapidly time-varying components. Finally, both types of sparse components are summed up to obtain the whole channel response. Numerical simulations as well as experimental results from field UWA communication data show that the proposed algorithm exhibits better performance in exploiting rapidly time-varying sparsity than the state-of-the-art compressive methods do under UWA channel.

As a time-frequency doubly selective channel, severe multipath, Doppler, as well as the large time-delay characteristics of the underwater acoustic (UWA) channel pose significant challenge to the research and design of UWA communication and network systems. To mitigate these negative factors, inherent sparsity contained in the UWA channel has been extensively investigated to improve UWA communication via a sparsity exploitation receiver. While the performance of the UWA sensor network is highly dependent on that of the physical layer, there are few investigations reported on exploiting channel sparsity from the viewpoint of UWA networking. In this article, a UWA sensor network adopting the sparsity exploitation physical layer is evaluated based on the network simulator 3 (NS-3) simulation tool. The simulation time-varying channel is generated by incorporating the Bellhop channel model with the statistical characteristics extracted from experimental shallow water channels. Three types of physical layers, i.e., those do not adopt sparse exploitation, adopting compressed sensing (CS), as well as the dynamic CS (DCS) technique, are employed for evaluation and comparison of network behavior under different media access control (MAC) protocols. The evaluation results verify the effectiveness of sparsity exploitation in improving UWA sensor network performance in the presence of time variations, while giving a quantitative comparison between enhancement achieved by the CS and DCS sparsity exploitation.

For deep-sea underwater acoustic (UWA) communication, large multi-path time delay spread, that caused by spatial divergence effects of acoustic propagation along the deep-sea distance-depth dimension, exert extremely adverse influence on communication performance. Inspired by the fact that the large delay spread deep-sea channels tend to be clustered, and each cluster of which varies independently with respect to receiving element as well as time delay, in this paper a multi-path clusters (MCs) joint equalization approach is proposed to explore the spatial-temporal diversity of large delay spread deep-sea UWA channels. Firstly we design a compact m-sequence synchronization sequence to extract MCs along different receiving element and time delay while achieving frame synchronization. Then, a sparsity-aware proportionate-type adaptive iterative algorithm is formulated under the recursive least squares (RLS) framework, by which, equalization output of each spatial-temporal-wise MC is aligned and combined to achieve joint equalization gain. Simulation results demonstrate that the proposed approach is capable of yielding superior performance in terms of output signal-to-noise ratio (SNR) and bit error rate (BER) compared to the traditional equalization approaches under large delay spread channels. Finally, in deep-sea trial error-free UWA communication with a maximum data rate of 6000 bps at a distance of 20 km is achieved by a two-element receiver, further demonstrating the effectiveness of the proposed algorithm.

Enhancing the performance of single-carrier underwater acoustic (UWA) communication systems necessitates the development of accurate channel estimation techniques within the receiver. Among various approaches, the recursive least squares (RLS)-based channel estimation method has been extensively employed due to its rapid convergence and robust tracking capabilities. Over time, numerous enhancements have been incorporated into the RLS framework to further improve channel estimation performance for UWA systems. In this paper, a novel Bidirectional Joint Iterative l₁-RLS (Bi-Ji-l₁-RLS) algorithm is proposed to optimize channel estimation for single-carrier UWA communication systems. The proposed algorithm exploits bidirectional diversity and the inherent sparsity of UWA channels to achieve performance improvements. A comprehensive transient analysis is developed, jointly considering the bidirectional estimation mechanism and the l₁-norm constraint, which elucidates the operational behaviors and confirms the advantages of the Bi-Ji-l₁-RLS algorithm over the conventional l₁-RLS approaches. Simulation results further validate the theoretical analysis, demonstrating enhanced estimation accuracy. Moreover, experimental results obtained from undersea trials substantiate the practical effectiveness of the proposed algorithm, highlighting its moderate superiority over existing techniques in real-world UWA communication scenarios. Specifically, the proposed algorithm achieves the minimum bit error rate (BER) of 0.0832% and the maximum output signal-to-noise ratio (OSNR) of 12.6024 dB.