The pervasiveness of commercial Internet of Things (IoT) around the globe is expected to reach significant levels with the upcoming sixth generation of mobile networks (6G). Throughout the past years, wireless standardization units worldwide have been prominently active in the deployment and performance optimization of such IoT networks and fusing them with current and futuristic cellular networks. Nonetheless, the openness of wireless transmissions and the forecasted overwhelm in connected devices will provoke unprecedented security leakages and vulnerabilities. In addition to the key targets of the 6G and IoT, it has been of paramount importance to cater to decent and lightweight security mechanisms in ultra-massively connected heterogeneous networks. Recently, significant efforts have been made to pave the way for the integration of physical layer security (PLS) in contemporary and futuristic networks. The primary motivation behind its deployment resides in its low complexity and ability to provide information-theoretic secure transmissions, which alleviates the complexity burden caused by implementing complex cryptographic schemes. This survey overviews the recent advancement in PLS techniques with a particular interest in its application to the Internet of Things (IoT). We review essentially recent PLS techniques aiming at ensuring message confidentiality along with node/message authentication and malicious nodes’ detection, where their corresponding application scenarios and underlying pros and cons are discussed. On top of that, we explore recent findings in the incorporation of cutting-edge technologies at the physical layer, such as non-orthogonal multiple-access, reconfigurable intelligent surfaces, joint communication and sensing, and optical wireless/Terahertz communications in boosting confidentiality and authentication at the physical layer. Lastly, promising extensions and future directions are discussed based on the quantified pros and cons of each PLS category, opening up ways for timely research directions within the topic and current/future challenges faced by PLS.

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 paper presents a new collaborative location estimation method for wireless sensor networks (WSN), referred to as an iterative tree search algorithm (I-TSA). The proposed method is based on the grid search least square estimator (LSE), which provides efficient estimation in the presence of noisy received signal strength (RSS) range measurements. The complexity analysis of the I-TSA algorithm showed that the computational requirement by each unknown-location sensor node scales linearly with the number of its neighbouring nodes, and that only a small communication overhead is required until its location estimate converges. This, in contrast to centralised methods, such as maximum likelihood estimator (MLE) and multidimensional scaling (MDS), provides a feasible solution for distributed computation in large scale WSN. Furthermore, the performance of I-TSA, is evaluated with reference to the Cramér-Rao bound (CRB) and compared with MLE, MDS and MDS-MLE methods. The results showed that I-TSA achieves lower standard deviations and biases for various simulation scenarios.