Sensor-less adaptive optics based on stochastic parallel gradient descent (SPGD) is effective for the compensation of atmospheric disturbances in coherent free-space optical communication systems. However, SPGD converges slowly and easily falls into local extremes. Combining adaptive moment estimation and SPGD, we propose the AdamSPGD algorithm for efficient wavefront correction. Theoretical analysis and numerical simulations demonstrate that AdamSPGD can significantly increase the convergence speed, robustness, and dynamic ability, thereby more efficiently suppress the negative effects of atmospheric turbulence on mixing efficiency, bit error rate, and outage probability. Experimental results show that AdamSPGD reduces ∼50% of iterations. The improved performances make the proposed algorithm suitable for SLAO to improve the quality of optical communications.
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