We propose a chaotic region-optimized probabilistic constellation shaping (CRPCS) scheme to enhance the security and the resistance to turbulence for free-space optical (FSO) communications. For this approach, a four-dimensional hyperchaotic system generates a pseudorandom sequence to rotate and encrypt the constellation. Constellation distribution of short pseudorandom sequences behaves as the law of a non-uniform character. Grouping long pseudorandom sequences and counting the characteristics of constellation distribution can realize probabilistic constellation shaping with low and fixed redundant information. We demonstrate a 56 Gbyte/s coherent FSO communication system based on log-normal and Gamma–Gamma turbulence models with a key space of 10⁷⁵. The results show that the optical receiver sensitivity is improved by 0.3–1.1 dB, and the transmission distance is also improved by 3.2%–7.0% in different shaping cases.

Hybrid free space optical (FSO)/radio frequency (RF) system has emerged as a high-data-rate solution for the last mile access network. In this paper, we establish a hybrid FSO/RF testbed including an intensity modulation/direct detection (IM/DD) FSO subsystem with space diversity and a high-order quadrature amplitude modulation (QAM) RF subsystem with polarization diversity, respectively. Based on the testbed, we propose and experimentally validate an intelligent transmission system where the link selection and switching technology is implemented. In particular, we propose a gated recurrent unit (GRU) neural network enhanced by time attention mechanism for the hybrid system. The experimental results demonstrate that the proposed system can achieve the prediction of FSO channel fading with a high precision where absolute percentage error (APE) values lower than 3% account for up to 90% of the prediction results. The implemented intelligent hybrid system can significantly reduce the link switching frequency and link interruption duration. Then the BER is further verified on the testbed, and results show that the intelligent hybrid system can improve the BER from the order of 10-2 to the order of 10-3 during the time periods when link switching occurs.

Free-space optical (FSO) technologies face significant challenges from atmospheric turbulence, which can degrade transmission performance. Adaptive optics (AO) techniques offer a promising solution by compensating for turbulence-induced optical aberrations in real-time. In this paper, we propose a deep learning-based AO compensation scheme utilizing a mixed convolutional channel attention prediction network (MCCA-PNet). The network establishes a mapping relationship between distorted beam intensity information and atmospheric turbulence, enabling real-time compensation on a spatial light modulator. In order to address the challenge of limited datasets across diverse atmospheric conditions, we introduce a personalized federated learning approach named federated layer similarity aggregation algorithm (FedLaySim). The proposed method enables the exchange of feature information while preserving data privacy through the use of a layer similarity algorithm. Compared to conventional local training methods, personalized federated training enhances phase screen prediction accuracy by 1.98 dB. The average mode purity of the compensated vortex beams (VB) reaches 0.96. Furthermore, the applicability of our AO compensation scheme in actual, real-world environments is verified through the use of atmospheric simulation in an environmental chamber.

In this paper, we propose a chaotic block-matching and three-dimensional (C-BM3D) filtering algorithm to remove the noise and enhance the security in the turbulent channel of free space optical (FSO) communication. We experimentally demonstrate the performance of C-BM3D by comparing it with chaotic non-local means filtering (C-NLM), chaotic Gaussian filtering and chaotic Median filtering based on Log-normal and Gamma-Gamma turbulence models. The results show that the peak signal-to-noise ratios (PSNRs) of C-BM3D in the weak turbulence under Log-normal and Gamma-Gamma models are up to 96.2956 and 93.2853, respectively. The C-BM3D also achieves superior image similarity in Log-normal turbulent channel, with its structural similarity index measures (SSIMs) nearly equal to 1. Additionally, the signal-to-noise ratio (SNR) of C-BM3D ranks the highest, and its bit error rate (BER) improves by at least 15 dB compared to that of the other three algorithms. The experimental results indicate that the C-BM3D can be a good candidate for the next generation of FSO communication in security and turbulence resistance.

In this paper, we propose a method to encrypt the permutation information (PI) and insert the synchronization head based on digital chaos and constellation shaping for orthogonal frequency division multiplexing-free space optical (OFDM-FSO) communication. Probabilistic shaping technology can improve laser emission efficiency, but it will generate the PI, which, transmitted separately, will occupy channel bandwidth. Therefore, we use a digital chaotic algorithm to encrypt the PI and insert it into the synchronization head. This processing reduces the occupation of the PI on communication bandwidth and improves the security of the transmission system. The PI can be converted into a binary bit stream and encrypted by the pseudo-random binary sequence (PRBS) generated by a 1-dimensional chaotic map amplifier (1-DCMA). In the case of regional probabilistic shaping, it can improve by 3.8-10% transmission distance. The results show that the proposed method has about 0.8-1 dB improvement in the received optical power higher than the original model. The synchronization head assisted the chaotic PI can not only enhance security but also improve the performance of transmission bit error rate (BER).