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Emerging optical wireless communication (OWC) and LiFi require an ever-increasing bandwidth and decreasing size of the receiver modules compatible with mobile communication. This leads to using arrayed photodetector (PD) solutions for the receiver. However, the classical imaging solutions (e.g., convex lenses) struggle to achieve the required optical concentration at mobile form factors. In comparison, the non-imaging solutions (e.g., compound parabolic concentrators (CPCs)) provide poor uniformity of the irradiance distribution at the PD plane that can impair the link performance in the arrayed PD receivers. This paper proposes a novel approach using a freeform lenslet concentrator array to achieve an enhanced gain at a 5- degree field-of-view (FoV) compared to existing standard imaging optics solutions. The design also maintains a better irradiance uniformity and smaller refracted beam angle than the nonimaging solutions. Making it a promising optical solution that can help bridge the gap between imaging and non-imaging optics for high bandwidth arrayed PD receivers for mobile LiFi and OWC applications

In this paper we propose a novel simulation tool for indoor Light Fidelity (LiFi) networks based on Wavelength Division (WD) with real optical filters characteristics. Firstly we present the measured passband spectra of optical filters, along with a system model validation relying on such acquired spectra. Secondly, we propose a simulation tool developed to extend the work of adaptive wavelength division multiple access to the multiple-input multiple-output case, suitable for conducting Monte Carlo simulations. Then, we validate such tool by considering an example scenario with fixed positions and orientations, including increasing number of users in an indoor LiFi network using WD. In order to better clarify the interference contributions to the quality of service provided, we consider the first user as reference, and evaluate how the presence of progressively higher number of users in its vicinity impacts the interference that the main user is experiencing. We then analyse how the signal-to-interference-plus-noise ratio, interference-to-noise ratio and signal-to-interference ratio figures of the main user change depending on how many interfering users are included in the considered scenario.

In this paper, multi-tier LiFi networks are studied in terms of energy efficiency (EE) and spectral efficiency (SE), which are crucial metrics for LiFi system design. We derived a closed-form expression of the user association probability for different tiers using stochastic geometry based Poisson Voronoi Tessellation (PVT) LiFi network. The performance metrics of the network, EE and SE, are analyzed in terms of different parameters such as transmit power and Lambertian index. Performance evaluations and numerical results show that multi-tier LiFi networks have an optimum transmit power in which EE is maximized. Besides, increasing the transmit power does not increase SE after passing a threshold point. The resulting trade-off between EE and SE is presented. &nbsp

The central part of the Shaluli Mountains is located in the Ganzi area, Sichuan Province, China, bordered by the Jinsha River and adjacent to Tibet. Frequent avalanches pose a serious threat to human activities and engineering construction such as the Sichuan-Tibet Railway under construction. Therefore, the evaluation of avalanche susceptibility in this area can not only help define the spatial pattern of avalanches on the Qinghai-Tibet Plateau but also provide references for the recognition and early warning of regional avalanche disasters. In this study, avalanche samples were selected by remote sensing interpretation supplemented by a detailed field survey, GIS spatial analysis, and data mining. Two statistical models [evidence confidence function (EBF) and certainty coefficient (CF)] combined with two machine learning models [logistic regression (LR) and multilayer perceptron (MLP)] were used to establish four integrated models (EBF-LR, CF-LR, EBF-MLP, and CF-MLP) as well as the traditional frequency ratio model (FR) for avalanche susceptibility evaluation. Finally, the results were checked for accuracy by Kappa coefficients and ROC curves. The CF-MLP (Kappa = 0.606, AUC = 0.910) model was the best avalanche susceptibility evaluation model for this study, the FR (Kappa = 0.584, AUC = 0.894) model had the next highest accuracy, and the combination of the CF algorithm and the machine learning model performed better than the EBF. The most important influencing factors were elevation, slope orientation, terrain moisture index, and January average temperature. The five models showed a high degree of consistency in the sensitivity to topographic factors during the evaluation of susceptibility. The avalanche susceptibility zoning map based on the CF-MLP model was obtained by the natural breakpoint method, and the areas with very high and high susceptibility accounted for about 10.01% and 15.33% of the total area, respectively.

Energy efficiency is one of the main benchmarks of performance in visible light communication. Achieving high energy efficiency in a link is a challenging task when high data throughput is required. A promising approach to tackling this challenge is using multiple-input-multiple-output (MIMO) systems, which use the spatial domain for information encoding. A novel modulation scheme called Flexible light emitting diode (LED) index keying (FLIK) can harness high spectral efficiency by utilising active and inactive LED states. The high spectral efficiency, together with a straightforward encoding, makes FLIK based design a promising candidate for high energy efficiency and data throughput solutions. However, the system’s performance based on FLIK depends heavily on beam selection participating in the link, which can significantly vary with the channel conditions subject to the user’s position and orientation. In a dynamic use case scenario, a fast beam selection and selection re-adjustment are vital for an optimal use case. This study examines the performance of beam selection based on a maximal signalto-noise ratio (SNR) criterion in angle diversity hemispherical transceiver systems. In this paper, a random orientation system model for FLIK is considered. The simulations are then performed considering maximal SNR and maximal Euclidean distance criteria. The performance is evaluated in terms of achievable data throughput. A selection method, based on the maximal SNR, is compared to a method based on maximizing Euclidean distance. The numerical results show that for both the fixed and random orientation cases, a beam selection based on maximal SNR performs as well as the one based on Euclidean distance. This observation is valid up to 25 degrees of beam halfintensity angle, therefore, validating the use of maximal SNR condition in such systems