The foundation of any smart city requires an innovative and robust communication infrastructure. Many research communities envision free-space optical communication (FSO) as a promising backbone technology for the services and applications provided by such cities. However, the channel through which the FSO signal travels is the atmosphere. Therefore, the FSO performance is limited by the local weather conditions. The variation in meteorological variables leads to variations of the refractive index along the transmission path. These index inhomogeneities (i.e., atmospheric turbulence) can significantly degrade the performance of FSO systems. Thus, a practical implementation of the FSO link must carefully consider the atmospheric turbulence effect. This paper aims to investigate the feasibility of FSO communication for NEOM, a promising smart city in Saudi Arabia. We study the effect of weather conditions on FSO links using the micrometeorology model, taking into account actual weather data. The FSO performance in winter and summer was compared in terms of the bit error rate, signal-to-noise ratio (SNR), link availability, and transmission distance. The study shows that the atmospheric turbulence strength is moderate and strong in winter and summer, respectively. The temperature has the biggest impact on the FSO system when compared to the other meteorological elements included in this study. Furthermore, at transmission distances less than 300 m, atmospheric turbulence does not significantly affect the FSO for the operating wavelength of 1550 nm. Furthermore, it has been shown that at transmission distances greater than 300 m, the SNR in summer is more than 18% higher than in winter. The findings of this research enable understanding of the effect of turbulence caused by NEOM weather on the FSO link, thus assisting engineers in establishing a reliable FSO backbone link by adjusting the relevant parameters.

There has been significant interest in free-space optical (FSO) communication by the research community in recent years. This is due to its high data rate, unlicensed spectrum, low cost, and immense security for FSO systems. Due to these advantages, FSO can have broader applications that extend from terrestrial to satellite communication. Atmospheric turbulence (AT) induced fading is a primary problem in the FSO link since it significantly impairs its performance. Atmospheric turbulence occurs due to the random variation of the air refractive index with time. Several statistical models are introduced to characterize the AT. The Log-normal (LN) model represents weak and moderate turbulence, and the Gamma-Gamma (G-G) model is employed for strong turbulence. These models are used with the effect of weather attenuation, geometric losses, and misalignment errors. One possible solution is channel coding, such as low-density parity-check (LDPC) codes. This paper proposed employing Weighted Bit Flipping (WBF) and Implementation Efficient Reliability Ratio Weighted Bit Flipping (IERRWBF) decoding techniques to improve FSO link performance. The results show a superior improvement in the bit error rate (BER) than the uncoded FSO system. In addition, the obtained results prove that the IERRWBF technique is more optimized than WBF from the point of the number of iterations, especially in weak and moderate turbulence FSO channels. In the calculation of decoders processing time, the WBF maintained lower decoding time than the IERRWBF technique, while in higher Eb/Nos, they have the same level. The same response for both techniques in the case of resultant throughput. Finally, both methods are evaluated from the point of convergence. IERRWBF technique achieved faster convergence than WBF in all FSO channels under study.

Wireless body area network (WBAN) is a promising network aiming at enhancing the communication in medical applications. It is adopted by medical organizations due to its flexibility in remotely monitoring patient health status. WBANs suffer from many limitations due to excessive channel impairments. Low density parity check (LDPC) codes are proposed to mitigate WBAN's impairments concerning the bit error rate, complexity, and dissipated energy. In this paper, a comprehensive performance analysis of various LDPC decoding algorithms is used to improve communication and reduce complexity in implant to implant WBAN channel. Moreover, a novel low complex LDPC decoding algorithm, which has a performance close to soft decision and a decoding time close to hard decision algorithms is proposed to minimize the dissipated energy. The proposed algorithm can be classified as a hybrid decision algorithm. The results demonstrate extensive analysis and comparisons between hard, soft, and hybrid decision algorithms.

In recent years, much research has been devoted to free-space optical communication (FSO). The unregulated spectrum, low implementation costs, and robust security of FSO systems all are of great importance which lead to a wide range of applications for FSO links, from terrestrial communications to satellite communications. However, the fundamental limitation with FSO links is atmospheric turbulence (AT) caused by fading, significantly reducing link performance. Random phenomena are the best characteristic of atmospheric turbulence caused by changes in the air’s refractive index over time. Numerous probability density functions of the AT models were presented to model the randomness in AT channels. The Log-Normal (LN) channel model is for weak atmospheric turbulence, while the Gamma–Gamma (G–G) channel is selected for moderate and strong atmospheric turbulence. The impacts of geometric losses, attenuation due to weather, and errors due to misalignment are addressed using LN and G–G channels. Channel coding is one of the possible solutions for mitigating such FSO channel impairments as the low-density parity check (LDPC) codes. In this article, the Weighted Bit Flipping (Algorithm (1)), Implementation Efficient Reliability Ratio Weighted Bit Flipping (Algorithm (2)), and Min-Sum (Algorithm (3)) algorithms are compared and evaluated against FSO atmospheric turbulence channels. In addition, two novel algorithms are proposed to enhance the complexity or Bit Error Rate performance of LDPC decoding over FSO channels. The results showed an impressive improvement of the coded FSO system by employing the proposed algorithms compared to the existing LDPC decoders for FSO communications from the point of all comparison parameters.