Turbulence Resistant Dual-Aperture Receiver With a Sparse Dual-Polarization Triple-Branch Network in Underwater Visible Light Communication

The sixth-generation mobile communication is committed to creating a large-capacity, low-latency, three-dimensional communication network encompassing space, air, land, and sea. Visible light communication (VLC) uses carriers with wavelengths from 380 nm to 760 nm for information transmission, offering a spectrum of 400 THz. Besides, visible light falls within the underwater transmission window, which offers significant potential for sea-based communication network construction. However, underwater visible light communication (UVLC) faces the effects of turbulence, device nonlinearity, attenuation, and noise, which limit the increase of the capacity of UVLC. To address the effects of turbulence, considering that turbulence has different effects on different polarization directions, the received signal can be better reconstructed by increasing the observation dimension, like observing the signal in multiple polarization directions. We proposed the use of circularly polarized light for transmission with a dual-aperture receiver, where the dual apertures detect the horizontally and vertically polarized components of the light beam, respectively. For the fusion of the two received signals, and in order to resist undesirable factors such as device nonlinearity and high-frequency attenuation, we designed a sparse dual-polarization triple-branch network (S-DPTBN) for signal reconstruction and recovery. The sparsification reduces the complexity and improves the robustness of the network, and the triple-branch design can fully extract the information of the horizontal and vertical polarizations as well as the weighted sum of the two. To enhance the communication capacity, we integrated an 8-wavelength laser emission module for signal transmission. Finally, experimental results confirmed that the proposed system achieved data rates of 144.90 Gbps, 143.50 Gbps, and 140.70 Gbps in conditions of no turbulence, medium turbulence, and strong turbulence, respectively, which had an improvement of 14.00 Gbps, 14.00 Gbps, and 13.30 Gbps over traditional point-to-point systems with deep neural network-based equalizers.