Free-space optical communications (FSO) propagated over a clear atmosphere suffers from irradiance fluctuation caused by small but random atmospheric temperature fluctuations. This results in decreased signal- to-noise ratio and consequently impaired error performance. In this paper, the error performance of the FSO using a subcarrier intensity modulation (SIM) based on a binary phase shift keying scheme in clear but turbulent atmosphere is presented. To evaluate the system error performance in turbulence regimes from weak to strong, the probability density function of the received irradiance after traversing the atmosphere is modelled using the gamma-gamma distribution and the effect of turbulence induced irradiance fluctuation is mitigated using spatial diversity.

Today’s air traffic management (ATM) system evolves around the air traffic controllers and pilots. This human-centered design made air traffic remarkably safe in the past. However, with the increase in flights and the variety of aircraft using European airspace, it is reaching its limits. It poses significant problems such as congestion, deterioration of flight safety, greater costs, more delays, and higher emissions. Transforming the ATM into the “next generation” requires complex human-integrated systems that provide better abstraction of airspace and create situational awareness, as described in the literature for this problem. This paper makes the following contributions: (a) It outlines the complexity of the problem. (b) It introduces a digital assistance system to detect conflicts in air traffic by systematically analyzing aircraft surveillance data to provide air traffic controllers with better situational awareness. For this purpose, long short-term memory (LSTMs) networks, which are a popular version of recurrent neural networks (RNNs) are used to determine whether their temporal dynamic behavior is capable of reliably monitoring air traffic and classifying error patterns. (c) Large-scale, realistic air traffic models with several thousand flights containing air traffic conflicts are used to create a parameterized airspace abstraction to train several variations of LSTM networks. The applied networks are based on a 20–10–1 architecture while using leaky ReLU and sigmoid activation function. For the learning process, the binary cross-entropy loss function and the adaptive moment estimation (ADAM) optimizer are applied with different learning rates and batch sizes over ten epochs. (d) Numerical results and achievements by using LSTM networks to predict various weather events, cyberattacks, emergency situations and human factors are presented.

Accurate indoor positioning is becoming increasingly important, especially in highly automated industrial environments with robots. In addition, LED-based lighting is also being used more and more frequently in such application fields. In the present work, the possibility to exploit the LED lighting infrastructure with a novel approach for implementing an accurate indoor positioning system is investigated. For this purpose, a demonstrator luminaire LEDPOS is proposed and evaluated that combines visible light sensing based on backscattered reflections to accurately estimate the two-dimensional position of a retroreflective foil at the floor while providing simultaneously an unimpaired room illumination. In particular, the same LED elements are shared for illumination and for the sensing functionality. Furthermore, the algorithm for data evaluation and position determination is based on a machine learning approach that is implemented on the edge in the luminaire. Thus, the presented approach allows for a simple and cost-efficient implementation in different applications. The experimental characterization of the LEDPOS demonstrator in a real-world scenario shows that a very good positioning accuracy can be achieved, in which the average error for the two-dimensional position of the retroreflective foil within an area of 0.64 m ² remains in the range of 3 cm.

Optical wireless networks realized by means of gigabit optical wireless communication (OWC) systems are becoming, in a variety of applications, an important alternative, or a complementary solution, to their fiber-based counterparts. However, performance of the OWC systems can be considerably degraded in periods of unfavorable weather conditions, such as heavy fog, which temporarily reduce the effective capacity of the network. In this paper, we focus on optical wireless mesh networks that use terrestrial links (called FSO - free-space optical - links) composed of several parallel full-duplex FSO systems, and present two complementary solutions that together provide a means to maximize network traffic performance in various weather conditions encountered during network operation. The first solution is a method for estimating the degradation of the effective FSO link capacity in adverse weather conditions such as fog, rain and snow (called the weather states in this paper). The second solution is an optimization model aiming at maximizing the network traffic throughput for a given list of weather states, derived from the conducted measurements. The model assumes the so-called affine flow thinning (AFT) traffic routing and protection mechanism capable of controlling the end-to-end traffic flows in response to fluctuations of capacity available on FSO links caused by changing weather conditions. The proposed link capacity modeling approach and the elaborated optimization model are verified through an exhaustive numerical study, illustrating the trade-off between the increase of traffic performance of the FSO networks and the corresponding cost of additional OWC systems.

A physical-layer secure data encryption algorithm is proposed and demonstrated using chaotic constellation mapping associated with probabilistic shaping (PS) for orthogonal frequency division multiplexing passive optical networks (OFDM-PONs). The constellation of the encrypted data is uniformly distributed after chaotic diffusion in quadratic-amplitude modulation (QAM) mapping, to eliminate the statistical characteristics, where a key space of ~10 ²³¹ is created by a 4-dimensional hyper digital chaos. Moreover, PS is introduced to improve the OFDM signal transmission. A 9.4 Gb/s encrypted PS-16-QAM OFDM signal transmission is successfully demonstrated over 20 km standard single-mode fiber (SSMF), where the gain of receiver sensitivity is ~2 dB (bit-error rate @ 10 ^-3 ) using PS.

In this paper, average bit error rate (BER) and outage probability are analysed in the free-space optical (FSO) system employing subcarrier intensity modulation (SIM) with differential phase shift keying (DPSK). The FSO channel is described by the lognormal atmospheric turbulence and the pointing error effects. Closed-form analytical expressions for the average BER and outage probability are proposed. Furthermore, the numerical results of the proposed form are presented and compered with the numerical solution of the integral form.