Abstract
In the sixth-generation communication (6G), wireless communication will cover not only conventional air links but also underwater links. Underwater visible light communication (UVLC) is an expected technique that achieves a high data rate. However, UVLC systems suffer from severe nonlinear distortions for the high-power transmitting, thus nonlinear compensation is vital to the system. Carrier-less amplitude and phase (CAP) modulation is a promising modulation, especially for the scenes with high nonlinear effects. In this paper, for the first time, we proposed a constellation optimization method for the UVLC system supporting the native artificial intelligence in 6G. The proposed framework, based on the complete process of the CAP modulation and demodulation, fulfills an end-to-end learning scheme with a neural network at the transmitter side and the conventional demodulation processes at the receiver side. A loss function is further designed to support the training without needing a fixed signal-to-noise ratio (SNR). The proposed framework is simulated and then tested in an experiment. In a 1.2-meter nonlinear UVLC channel, compared with 1.5 Gbit/s supported by the conventional grid encoding, the proposed method brings an extra 200 Mbit/s data rate.
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Acknowledgements
This work was partially supported by National Natural Science Foundation of China (Grant Nos. 61925104, 62031011, 62171137), Natural Science Foundation of Shanghai (Grant No. 21ZR1408700), and the Major Key Project of PCL.
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Jia, J., Zhang, J. & Chi, N. Constellation shaping optimization for nonlinearity mitigation in CAP UVLC system. Sci. China Inf. Sci. 66, 192305 (2023). https://doi.org/10.1007/s11432-022-3643-y
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DOI: https://doi.org/10.1007/s11432-022-3643-y