Abstract

In this paper, we first utilize the interleaved single-carrier frequency division multiplexing (I-SC-FDM) scheme with a novel sparse weight-initiated deep neural network (SWI-DNN) equalizer for underwater optical communication (UWOC) systems. In addition to the superior characteristics of I-SC-FDM over the original OFDM and localized SC-FDM (L-SC-FDM), such as lower peak-to-average power ratio (PAPR) and lower computational complexity, the implementation of a special sparse weight-initiated (SWI) structure can significantly reduce the necessary training epochs up to 10.3%, which enables the proposed SWI-DNN equalizer to outperform the traditional random weight-initiated DNN equalizer. Besides, further pruning operation can dramatically enhance the final sparsity of the SWI-DNN equalizer to 96.88% at the expense of an inappreciable performance penalty, thereby effectively saving occupied computing resources. Following this, a data rate of up to 660 Mbps over a 90-m underwater transmission can be achieved in a standard 50-m swimming pool, with a relatively low received optical power of -31.12 dBm (at the BER of 3.8 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> ). Such a data rate is 17.9% higher than that obtained with a common hybrid time-frequency domain (TFD) equalizer. Moreover, the computational complexity of the SWI-DNN equalizer after pruning operation is only 11.83% of that of the hybrid TFD equalizer and can still support a 625-Mbps transmission. This is the first time to employ I-SC-FDM combined with an SWI-DNN equalizer for long-distance high-speed UWOC transmission, and it can be highly beneficial to the cost-sensitive and power-sensitive systems in future deployment.

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