A realistic channel model is vital for designing, optimizing, and evaluating unmanned aerial vehicle (UAV)-to-ground (U2G) communication systems. This paper presents a comprehensive U2G ultra-wideband (UWB) channel model by considering the large-scale fading (LSF), including path loss (PL), shadow fading (SF), and airframe shadowing (AS). The effects of carrier frequency, bandwidth, building distribution, and UAV airframe structure on the LSF are fully studied. Different from the traditional bandwidth-independent PL calculation method, an extended closed-form expression for calculating PL is proposed to capture the new characteristics of ultra-wide bandwidth. The SF part is statistically described by a parametric lognormal model, and the built-up scenario-dependent parameters are predicted by a hybrid method with the ray-tracing and virtual scenario technologies. In addition, the AS part with respect to the airframe structure and posture variation is derived. It consists of the direct and reflected path components which are obtained by the deterministic and statistical approaches, respectively. The numerical simulations show that bandwidth, building distribution, and airframe structure have great influence on the LSF characteristics. For example, the fluctuation of received power can reach 30 dB due to the AS. The proposed model also shows its effectiveness and reliability by comparing with the RT and measured data, as well as the good compatibility with standardized models for some typical scenarios.

The load pressure on electrical power system is increased during last decade. The installation of new power generators (PGs) take huge time and cost. Therefore, to manage current power demands, the solar plants are considered a fruitful solution. However, critical caring and balance output power in solar plants are the highlighted issues. Which needs a proper procedure in order to minimize balance output power and caring issues in solar plants. This paper investigates artificial neural network (ANN) and hybrid boost converter (HBC) based MPPT for improving the output power of solar plants. The proposed model is analyzed in two steps, the offline step and the online step. Where the offline status is used for training various terms of ANNs in terms of structure and algorithm while in the online step, the online procedure is applied with optimum ANN for maximum power point tracking (MPPT) using traditional converter and hybrid converter in solar plants. Moreover, a detail analytical framework is studied for both proposed steps. The mathematical and simulation approaches show that the presented model efficiently regulate the output of solar plants. This technique is applicable for current installed solar plants which reduces the cost per generation.

Optical communication networks (OCNs) provide promising and cost-effective support for the ultra-fast broadband solutions, thus enabling them to address the ever growing demands of telecommunication industry such as high capacity and end users’ data rate. OCNs are used in both wired and wireless access networks as they offer many advantages over conventional copper wire transmission such as low power consumption, low cost, ultra-high bandwidth, and high transmission rates. Channel effects caused by light propagation through the fiber limits the performance, hence the data rate of the overall transmission. To achieve the maximum performance gain in terms of transmission rate through the OCN, an optical downlink system is investigated in this paper using feed forward equalizer (FFE) along with decision feedback equalizer (DFE). The simulation results show that the proposed technique plays a key role in dispersion mitigation in multi-channel optical transmission to uphold multi-Gb/s transmission. Moreover, bit error rate (BER) and quality factor (Q-factor) below ${10}^{-5}$ and above 5, respectively, are achieved with electrical domain equalizers for the OCN in the presence of multiple distortion effects showing the effectiveness of the proposed adaptive equalization techniques.

With the fast development of unmanned aerial vehicles (UAVs), reliable UAV communication is becoming increasingly vital. The channel knowledge map (CKM) is a crucial bridge connecting the environment and the propagation channel that may visually depict channel characteristics. This paper presents a comprehensive scheme based on a UAV-assisted channel measurement system for constructing the CKM in real-world scenarios. Firstly, a three-dimensional (3D) CKM construction scheme for real-world scenarios is provided, which involves channel knowledge extraction, mapping, and completion. Secondly, an algorithm of channel knowledge extraction and completion is proposed. The sparse channel knowledge is extracted based on the sliding correlation and constant false alarm rate (CFAR) approaches. The 3D Kriging interpolation is used to complete the sparse channel knowledge. Finally, a UAV-assisted channel measurement system is developed and CKM measurement campaigns are conducted in campus and farmland scenarios. The path loss (PL) and root mean square delay spread (RMS-DS) are measured at different heights to determine CKMs. The measured and analyzed results show that the proposed construction scheme can effectively and accurately construct the CKMs in real-world scenarios.

A dramatic increase in user and capacity demands has been noted after the COVID-19 pandemic. These challenges have damaged the 5G communication system mobility. Therefore, developing mobility and enhancing capacity transmission of 5G advanced services are the focused research gaps in the current era. In this paper, the free space optics (FSO) link is modeled with wavelength division multiplexing (WDM) technology based optical fiber system, purposing to enhance the 5G capabilities in multi-channel, high distance, and bidirectional transmissions. In addition, the presented hybrid FSO-WDM supported optical fiber network is analyzed for 4, 8, and 16 × 10 Gbps downlink and uplink transmission. The paper also includes the mathematical discussion of merged fiber length (SMF = 30 km) and FSO (600 m) with improved mobility management. In another contribution, the tolerance against Rayleigh backscattering (RB) noises is developed through various wavelengths of downlink and uplink channels. Finally, we perform the simulation analysis and reliability of the proposed structure for the 5G advanced communication system.