Quantifying Sparsity of Underwater Acoustic Channel: Field Measurement and Analysis

The inherent sparsity intrinsic to the underwater acoustic (UWA) channel has been a driving force behind substantial efforts toward improving UWA communication, i.e., exploring the sparsity characteristic in crucial aspects such as UWA channel estimation and UWA channel equalization. While extensive empirical evidence obtained from comprehensive sea trial observations supports the recognition that assuming sparsity as a fundamental attribute of the UWA channel is well-founded, the current evaluation measures used to assess the sparsity of UWA channel primarily rely on subjective analysis, lacking a comprehensive analysis and evaluation of measurement indicators tailored specifically for quantifying sparsity in such channel. In this article, the issue of measuring UWA channel sparsity is addressed from the perspective of real-world experimental observation. We evaluate three measures for analyzing UWA channel sparsity: the number of multipath components (MPCs), the Gini index, and the Ricean
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factor. Although these measures have been used individually in studies related to radio or UWA wireless channel, a comprehensive comparison for quantifying the sparsity of UWA channel is yet to be established. To bridge this gap, we conduct a measurement and analysis of UWA channel sparsity in a shallow water acoustic communication scenario in the real world. Using real-world data collected at a center frequency of 15.5 kHz in Xiamen Harbor, we assess the performance of the aforementioned measures in quantifying UWA channel sparsity with respect to marine environmental behaviors. Our findings demonstrate that these sparsity measures show consistent and reliable results in terms of UWA channel sparsity quantification, which also points to the Gini index as the most suitable sparsity indicator from a practical point of view. Moreover, the relationship between the UWA channel sparsity and environmental behaviors, i.e., wind, tide, and wave, is analyzed and validated.