Design and Performance Analysis of NadamSPGD Algorithm for Sensor-Less Adaptive Optics in Coherent FSOC Systems

Abstract

Sensor-less adaptive optics (SLAO) based on stochastic parallel gradient descent (SPGD) is effective for the compensation of atmospheric turbulence in coherent free-space optical communication (CFSOC) systems. However, SPGD converges slowly and easily falls into local extremes. Therefore, we propose a novel NadamSPGD algorithm for efficient wavefront correction that combines Nesterov-accelerated adaptive moment estimation (Nadam) and SPGD. Specifically, Nesterov’s accelerated gradient momentum (NAG) and adaptive gain coefficients are integrated to conventional SPGD to accelerate its convergence speed and avoid converging to extremum points. Theoretical analysis, numerical simulations and experimental results demonstrate that NadamSPGD can increase the convergence speed by ~50% and significantly improve the robustness of parameters, and thus more efficiently suppress the negative effects of atmospheric turbulence on mixing efficiency (ME) and bit error rate (BER). Our algorithm also presents better dynamic performance under strong turbulence and high Greenwood frequency conditions, and it is more suitable for real-time SLAO systems. This study proves that the NadamSPGD algorithm is suitable for SLAO in the CFSOC system and is a viable substitute for SPGD to improve the quality of optical communications.