In dual-wavelength free-space optical communication systems, the wavefront distortion differences caused by the wavelength difference of the signal and beacon lights cannot be completely corrected. In this study, according to the method of geometric optics, the relationship between the wavefront phases of the signal and beacon lights is analyzed by establishing a mathematical model of the cross-correlation ratio of the arrival-angle fluctuation and phase relationship of different Gaussian-beam wavelengths under weak turbulence near the surface. The numerical results show that after Gaussian beams of different wavelengths propagate through the same atmospheric channel, the cross-correlation number of the arrival-angle fluctuation decreases with an increase in the wavelength difference, waist radius, and turbulence intensity, and increases with an increase in propagation distance. The beam-wavefront phase difference increases with an increasing wavelength difference. Finally, a wavefront distortion correction experiment of a dual-wavelength adaptive optical system verified the correctness of the wavefront phase-difference relationship between the signal light and beacon light established in this study.

Atmospheric turbulence causes signal beam wavefront distortion at the receiving end of a coherent detection system, which decreases the system mixing efficiency. Based on the coherent detection theory, this study establishes a mathematical model of wavefront distortion with mixing efficiency and mixing gain. It also analyzes the improvement limits of wavefront correction on mixing efficiency and mixing gain under different atmospheric turbulence intensities and experimentally measures them. Simulation results show that the mixing efficiency can be improved to 51%, 55%, and 60% after correcting for tilt, defocus, and astigmatism terms, respectively, when turbulence intensity D/r₀ is 2. The mixing gain with homodyne detection is 3 dB higher than heterodyne detection. Meanwhile, the wavefront correction orders required for optimal mixing efficiency are higher than the heterodyne correction order. In the experiment, Haso4 NIR + DM 40 was used, and the turbulence intensity D/r₀ was 2. After the closed-loop control algorithm corrects the tilt, defocus, and astigmatism terms, the indoor experimental results showed that the mixing efficiency is improved to 36%, 47%, and 62%, respectively. The outdoor experimental results showed that the mixing efficiency improved to 36%, 51%, and 68%, respectively.

This paper proposes a non-common-view axis alignment method for the alignment requirements of airborne laser communication systems. The system consists of a ground transmitting end and an airborne relay terminal. The ground transmitting end uses a camera and a pan-tilt for image tracking, while the airborne relay end uses a two-dimensional mirror to control the beam to achieve non-common-view axis alignment between the transmitting and receiving sides. The working principle and process of both the transmitter and receiver of the non-common-view axis alignment system for airborne laser communication were compared with traditional wireless optical alignment methods. The design process of the two-dimensional mirror used in this paper is introduced, the scanning trajectory of the two-dimensional mirror is simulated and analyzed according to the beam scanning principle, and the field experiment link is set up to carry out the airborne laser communication experiment. The experimental results show that when the link distance is 10 m, the tracking errors of the system in the azimuth and pitch directions are 19.02 µrad and 22.35 µrad respectively, and the amplitude of the electrical signal output by the signal detector is 84.0 mV; When the link distance is 20 m, the tracking errors of the system in the azimuth and pitch directions are 39.66 µrad and 33.94 µrad respectively, and the amplitude of the electrical signal output by the signal detector is 23.0 mV. Using this method, the alignment can be completed without data return, and the establishment of the reverse link can also be realized while the transmission link is quickly established, and there is no need for an air stability platform. The feasibility of the application of the non-common-view axis alignment method to the airborne laser communication system is verified.

This paper addresses the handover challenge in indoor visible light communication and Wi-Fi heterogeneous networks, proposing an adaptive handover strategy based on user trajectory prediction. Extracting meaningful and important location points from massive trajectory data for clustering, an improved hidden Markov model is used to predict the user’s next location by analyzing the patterns of the user’s historical mobile trajectory data. The Q-learning algorithm is then used to determine the optimal network handover based on the current network state, while a seamless handover protocol is introduced to ensure successful network transition and uninterrupted data transmission. Compared with the traditional STD-LTE handover scheme, the proposed algorithm can reduce vertical handover rates by up to 32% during fast walking. When indoor user connections increase, the algorithm can maintain high fairness and high throughput when indoor user connections increase, verifying that it is robust in different scenarios.

The vortex beam carrying Orbital Angular Momentum (OAM) has infinite orthogonal characteristic states, which theoretically can infinitely increase the communication transmission capacity, thus attracting much attention in the field of optical communication. Due to the large amount of data required for training each OAM mode, the increase in channel capacity leads to an exponential growth in the required data volume. At the same time, the phase wavefront distortion caused by atmospheric turbulence (AT) further increases the difficulty of OAM pattern recognition. This article introduces transfer learning into the field of OAM modal detection and establishes an OAM modal classifier for detecting the topological charge of distorted vortex beams. The influence of different data volumes, turbulence intensities, and propagation distances on the accuracy of OAM modal detection during the transmission of Laguerre Gaussian beams in atmospheric turbulent channels is studied, and the generalization ability of the model is analyzed. The results show that compared with traditional convolutional neural networks, the modal classifier proposed in this paper reduces the dataset size to 1/10 of the original and successfully improves the OAM detection accuracy by 15.84%. It also exhibits good generalization under unknown atmospheric turbulence strengths, providing a new approach for identifying OAM modes.

Aiming at the problem of large positioning errors in the boundary area, a new location fingerprint location method based on a fusion clustering algorithm is proposed. This clustering-based method embodies the idea of rough location first and then fine location. Firstly, the edge regions of the received signal strength (RSS) samples which are greatly affected by reflection are divided using the k-medoids algorithm, and then the center part is clustered via density-based spatial clustering of applications with noise (DBSCAN). In the actual location estimation stage, the points to be measured can only be located in one of the classified areas, and combined with the optimal k-nearest neighbor algorithm (WOKNN) to match the location. The results show that the average positioning error of the algorithm is 13 cm in an indoor environment of 5 m × 5 m × 3 m. Compared with the traditional method without clustering, the positioning accuracy of the edge area is increased by 21%, and the overall improvement is 33.8%, which proves that the proposed algorithm effectively improves the efficiency of real-time positioning and indoor positioning accuracy.