This paper introduces a novel free space optics (FSO) communication system for future-generation high-speed networks. The proposed system integrates orbital angular momentum (OAM) modes with an optical code division multiple access (OCDMA) technique. Two OAM beams are used ($L{G}_{0,0}$ and $L{G}_{0,10}$), each of which is used for transmitting three independent channels. Each channel is assigned by fixed right shift (FRS) codes and carries 10 Gbps of information data. The performance of the proposed model is evaluated under different foggy and dust storm conditions. Furthermore, the performance of two cities with different geographical locations, Alexandria city in Egypt and Srinagar city in India, is investigated to demonstrate its ability to be implemented in future generations. Bit error rate (BER), eye diagrams, received optical power (ROP), and channel capacity are used for studying the performance of the proposed system. The observed simulation results show successful transmission of 60 Gbps overall capacity with the longest propagation FSO range for Alexandria city, which is 1400 m. Because dust storms have a large attenuation when compared to different foggy conditions, the proposed model had the shortest propagation range of 315 m under low dust (LD), 105 m under moderate dust (MD), and 40 m under heavy dust (HD). Furthermore, the cloudy weather conditions that affect Srinagar city, which is considered a hilly area, make our suggested model achieve 1000 m.

This article proposes a new high-gain transformerless dc/dc boost converter. Although they possess the ability to boost voltage at higher voltage levels, converter switching devices are under low voltage stress. The voltage stress on active switching devices is lower than the output voltage. Therefore, low-rated components are used to implement the converter. The proposed converter can be considered as a promising candidate for PV microconverter applications, where high voltage-gain is required. The principle of operation and the steady-state analysis of the converter in the continuous conduction mode are presented. A hardware prototype for the converter is implemented in the laboratory to prove the concept of operation.

This paper proposes a multi-objective planning framework for electric vehicle (EV) charging stations in emerging power networks that move towards green transportation electrification. Four cases are investigated to study the impacts of EV integration on environmental and economic requirements. In order to facilitate the installation of EV charging stations, the proposed model is formulated to combine the planning models of renewable energy systems, energy storage systems (ESSs), thyristor-controlled series compensators, and transmission lines into the EV-based planning problem. The first objective function aims to maximize EVs’ penetration by increasing the networks’ capacity to supply charging stations throughout the day, whereas the second objective, on the other hand, emphasizes lowering the carbon dioxide emissions from fossil fuel-based generation units in order to benefit the environment. The third objective is to meet the financial requirements by lowering the initial investment and operating costs of the installed devices. The proposed model is written as a multi-objective optimization problem that is solved using the multi-objective version of the Gazelle optimization algorithm (MGOA). The efficiency of the MGOA was tested by solving a set of four benchmark test functions and the proposed problem. The obtained results demonstrated the MGOA’s superiority in solving multi-objective optimization problems when compared to some well-known optimization algorithms in terms of robustness and solution quality. The MGOA’s robustness was between 20% and 30% and outperformed other algorithms by 5%. The MGO was successful in outperforming the other algorithms in providing a better solution. The Egyptian West Delta Network simulations revealed a 250 MWh increase in the energy supplied to EVs when energy storage was not used. However, storage systems were necessary for shifting EV charging periods away from high solar radiation scenarios. The use of ESS increased greenhouse gas emissions. When ESS was installed with a capacity of 1116.4 MWh, the carbon emissions increased by approximately 208.29 million metric tons. ESS’s role in improving the EV’s hosting capacity grows as more renewables are added to the network. ESS’s role in improving the EV’s hosting capacity rises as more renewables are added to the network.

Free Space Optics (FSO) has emerged as a viable solution to meet the growing demand for high bandwidth, secure data transmission, and high speed. However, the FSO system is highly susceptible to environmental factors, with precipitation in particular having a significant impact on FSO links. Optical loss, phase fluctuation, and multipath fading of the received optical power are all caused by these external factors. From this perspective, to improve the system’s performance in such conditions, a novel image encryption technique based on the Choquet Fuzzy Integral (CFI) in conjunction with the integer wavelet transform is proposed. The security of the proposed method is demonstrated via analysis security on the one, and its efficacy in terms of transmission performance of an encrypted image over an FSO channel exposed to rainy weather conditions is analyzed on the other. Authentic meteorological data from two distinct cities are considered to demonstrate the model’s real-world applicability: Alexandria, Egypt, in Africa, and Jeddah, Kingdom of Saudi Arabia (KSA), in Asia. To evaluate the system’s performance, a variety of metrics such as FSO range, Signal-to-Noise Ratio (SNR), Peak Signal-to-Noise Ratio (PSNR), and the Structural Similarity Index Method (SSIM) are used. Furthermore, the findings from studying the impact of weather conditions reveal that, as the intensity of rainfall increases, the encrypted image experiences a reduction in its propagation range within the FSO channel. For example, under heavy rain (HR) conditions, the maximum FSO range for high-quality received encrypted images is 1055 m, which extends to 2290 m as rain intensity decreases (for light rain). In terms of the two cities, Jeddah, with its lower average rainfall intensity compared to Alexandria, allows the encrypted image to travel an additional 2400 m.

With the rapid evolution of security technology, small field-size elliptic curve-based point multiplication (PM) has gradually become obsolete, leading to the implementation of PM with large field sizes. From this perspective, in this article, through a novel algorithm-architecture co-design strategy, we propose an efficient implementation of the PM on the elliptic curve over GF(2 $^m)$ (particularly targeting large field sizes). To achieve an area-time-efficient elliptic curve cryptography (ECC) processor implementation on the field-programmable gate array (FPGA) platform, we have proposed a bottom-up approach based on three coherent interdependent layers of efforts. First, we proposed an efficient digit-serial versatile multiplier (DSVM) based on polynomial representation. The system is built using the four-way overlap-free Karatsuba algorithm (OFKA) and a modified radix-n interleaved multiplication (mRnIM) technique (for area and time complexities reduction). Of course, the efficiency of the proposed multiplier is demonstrated by the complexity analysis and comparison with the existing reported designs. Second, we have adopted the López–Dahab (LD) Montgomery PM algorithm to avoid data dependency and enhance signal control in the ECC design. Meanwhile, a series of resource optimization techniques have also been adopted for the proposed ECC processor to optimize the overall design efficiency further. Third, the proposed ECC PM architecture is then implemented on the FPGA platform, showing that the proposed ECC crypto-processor obtains the least area-delay product (ADP) among all the existing structures for the large field sizes.