This paper presents a new systematic survey of the free-space optical (FSO) system, highlighting its operations and applications in outdoor optical communication underlying its interaction with the environment. As the application portfolio of FSO technology grows, so does the need for a clear classification for FSO link configurations. Most existing surveys and classifications are single-level classifications using traditional survey methods, and thus not inclusive enough to accommodate recent and emerging changes and developments of different FSO link configurations and systems. To that end, this paper adopts a novel methodology based on statistical analysis using a natural language processing approach (NLP) to analyze, visualize, and interpret the researchers' trends of 5075 relevant literature published documents (journal papers, conference papers, books, etc.) from 2017 to Feb-2024. The process of summarizing and analyzing is encompassed by adopting hierarchal multi-level classifications for the key performance evaluations, motivations, challenges, and contributions related to FSO systems. The survey is started by understanding the key performance of FSO such as matrices models and mathematical models. Then, the survey process is followed by investigating the outdoor FSO applications (urban, satellite, smart city, military, healthcare, disasters, and sensing applications). We have relied on listing and dividing the outdoor FSO networks into sub-networks based on the FSO’s architectural structures (point-to-multipoint, mobile network, long-range transmission and heterogeneous). In turn, outdoor impairments are classified into two categories: 1) environmental factors (weather and atmospheric conditions) and 2) component systems (source types and mechanical issues). We demonstrate the impact of these impairments in terms of the optical phenomena (effects), such as scattering, reflection, refraction, absorption, shadowing, and consequences (outcomes), such as pointing error, misalignments, beam divergence, etc. Finally, multi-technical solutions are listed and analyzed based on the researchers' contributions, such as modulation, detection techniques, relay, array, and retroflectors. This paper is the first paper that adopts the statistical analysis approach for studying the FSO in outdoor applications, making this approach a good choice for future researchers to prioritize their decisions about future trends and target their improvements.

This study introduces a new design for an ultra-compact shared-aperture antenna utilizing a quarter-mode substrate integrated waveguide (QMSIW) cavity. The proposed antenna operates as a 4 × 4 multi-input multi-output (MIMO) system in three 5G/6G millimeter-wave (MMw) bands, while functioning as a single element antenna for a 5.5 GHz wireless fidelity Microwave (Mw) band. The antenna comprises four QMSIW cavity resonators; each QMSIW is loaded with dual slots to produce tri-band MMw operation at 28 GHz, 38 GHz, and 0.13 THz. The four cavities are arranged to reuse the entire aperture by creating a conventional open-loop antenna that operates at a frequency of 5.5 GHz. Simulation, measurement, and co-simulation results show that the proposed antenna has a quad-band operation and exhibits favorable characteristics. The measured scattering parameters validate the simulated ones over the four bands under consideration. The lowest values of the measured total radiation efficiencies are 80%, 73%, 62%, and 72% (co-simulation) within the four covered bands, respectively. The antenna peak gains are 1.8 to 1.85 dBi, 4.0 to 4.5 dBi, 4.3 to 4.5 dBi, and 6.5 to 6.6 dBi within the covered bands. Furthermore, the design satisfies MIMO and diversity conditions (envelope correlation coefficient and branch power ratio) over frequency bands of operation. All excellent results are achieved from an ultra-compact size in terms of footprint area (0.018${\lambda }_0^2$), where λ₀ represents the free space wavelength at 5.5 GHz. The antenna boasts an excellent reuse aperture utilization efficiency (RAU) of 92% and a large ratio frequency of 23, making it an ideal candidate for compact devices. With its superior performance, the proposed design is well-suited for a range ofs wireless communication systems, including mobile devices and the Internet of Things.

In this paper, which represents a fundamental step in ongoing research, a new smart low-energy dual-function half-mode substrate integrated waveguide cavity-interdigital capacitor (HMSIWC-DIC) antenna-based sensor is developed and investigated for remote frost and wildfire detection applications at 5.7 GHz. The proposed methodology exploits the HMSIW antenna-based sensor, a microfluidic channel (microliter water channel (50 μL)), interdigital capacitor technologies, and the resonance frequency parameters combined with machine learning algorithms. This allows for superior interaction between the water channel and the TE101 mode, resulting in high sensitivity (∆f/∆ε = 5.5 MHz/ε (F/m) and ∆f/∆°C = 1.83 MHz/°C) within the sensing range. Additionally, it exhibits high decision-making ability and immunity to interference, demonstrating a best-in-class sensory response to weather temperature across two ranges: positive (≥0 °C, including frost and wildfire) and negative (<0 °C, including ice accumulation). To address the challenges posed by the non-linear, unpredictable behavior of resonance frequency results, even when dealing with weak sensor antenna responses, an innovative sensory intelligent system was proposed. This system utilizes resonance frequency results as features to classify and predict weather temperature ranges into three environmental states: Early Frost, Normal, and Early Wildfire, achieving an accuracy of 96.4%. Several machine learning techniques are employed, including artificial neural networks (ANNs), random forests (RF), decision trees (DT), support vector machines (SVMs), and Gaussian processes (GPs). This sensor serves as an ideal solution for energy management through its utilization in RF-based weather temperature sensing applications. It boasts stable performance, minimal energy consumption, and real-time sensitivity, eliminating the necessity for manual data recording.