Free-space optical (FSO) communication is widely used in satellites, ships, aircraft, and ground stations due to its advantages of high speed, large capacity, good confidentiality, and strong anti-interference ability. Variable-beam divergence angle (VBDA) technology makes FSO systems more flexible; this has the benefits of higher acquisition probability, stronger tracking ability, wider communication link range, and lower energy consumption. In other words, the study of VBDA has both theoretical significance and practical relevance. This paper conducts a comprehensive search of relevant scientific databases, journals, conference proceedings, patents, and books to identify publications related to VBDA technology. We analyze these publications, classify and organize various VBDA techniques based on their respective methods. To the best of our knowledge, this is the first review of VBDA technology. In this paper, we first explain the basic principle of changing the beam divergence angle by employing the ABCD matrix, and further furnish a detailed overview of the methods used for VBDA along with their corresponding advantages and disadvantages. In addition, we provide a comprehensive summary of the research conducted using VBDA technology across different link types. Lastly, we identify the challenges and potential future research directions for VBDA technology.

A distributed antenna system (DAS) is very attractive, since it can reduce transmit power by shortening the distance between antenna elements (AEs) and the mobile station. This paper investigates the channel capacity of the DAS over a multi-path frequency-selective fading channel. We first show that the optimal power allocation solution to approaching the channel capacity is unrealistic for the practical DAS. Then, a near-optimal scheme is given through maximally tightening the upper bound of the channel capacity. Approximate analytical results are obtained through the use of the central-limit theorem. Both simulation and theoretical results are presented to show that the channel capacity can be greatly enhanced by the proposed power allocation schemes. Moreover, the bit error rate performance is analyzed for the proposed scheme.

In this paper, On-Off Keying (OOK) free-space optical (FSO) communication with coherent detection and double adaptive detection thresholds (CD-DADT) is proposed. The 3-bit encoding and double adaptive detection thresholds presented in the scheme can significantly improve the system performance, and there is no need of acquiring the instantaneous channel state information (CSI) and probability density function (PDF) of turbulence model. In order to enhance the accuracy of the threshold even further, decision-aided method is offered to set the second detection threshold. The PDFs of the detection thresholds and the average bit error rate (BER) of the system are theoretically derived. Numerical studies show that the performance of the system is comparable to the performance of the idealized adaptive detection system and the loss of signal-to-noise ratio (SNR) performance is only 1 dB at a BER of 10-9 over a lognormal turbulence channel with normalized standard deviation of irradiance σ=0.25 and phase noise with normalized variance $\sigma;_{\oslash}^{2}$ 2=0.07. Hence, this scheme can contribute to the performance improvement of the FSO system and its practical realization.

Relay-aided free-space optical (FSO) communication systems have the ability of mitigating the adverse effects of link disruption by dividing a long link into several short links. In order to solve the relay selection (RS) problem in a decode and forward (DF) relay-aided FSO system, we model the relay selection scheme as a Markov decision process (MDP). Based on a dueling deep Q-network (DQN), the DQN-RS algorithm is proposed, which aims at maximizing the average capacity. Different from relevant works, the switching loss between relay nodes is considered. Thanks to the advantage of maximizing cumulative rewards by deep reinforcement learning (DRL), our simulation results demonstrate that the proposed DQN-RS algorithm outperforms the traditional greedy method.

The error performance of the optical wireless communication (OWC) link suffers from the effects of atmospheric turbulence and pointing errors. The multi-input-multi-output (MIMO) system can combat the damage by transmitting diverse replicas of symbols to the receivers, i.e. the spatial diversity. However, different delays between the transceivers can introduce inter-symbol interference (ISI) which degrades the system performance. The delays during transmission are mainly caused by placing locations and optical path differences. This article proposes algorithms to mitigate the ISI based on machine learning techniques, including both neural networks and the genetic algorithm. In the case of multi-input-single-output (MISO) system, we propose an algorithm based on a bidirectional long short-term memory (LSTM) recurrent neural network (RNN), which works as an equalizer. In the case of single-input-multiple-output (SIMO) system, additional delayers are utilized to align the signals in different apertures. The problem of deducing the values of the delayers is considered as seeking the minimum value in a high-dimensional space. With the help of the genetic algorithm, optimal values of the delayers are maintained, which is named as GAD (genetic algorithm-based delayers). In a more general MIMO case, the GAD and LSTM equalizers are further combined to deal with the ISI issue in the asynchronous MIMO OWC systems, (i.e. GAD-LSTM). Both experimental and simulation results show the remarkable performance improvement of the proposed method over conventional methods.