The explosive popularity of small-cell and Internet of Everything devices has tremendously increased traffic loads. This increase has revolutionised the current network into 5G technology, which demands increased capacity, high data rate and ultra-low latency. Two of the research focus areas for meeting these demands are exploring the spectrum resource and maximising the utilisation of its bands. However, the scarcity of the spectrum resource creates a serious challenge in achieving an efficient management scheme. This work aims to conduct an in-depth survey on recent spectrum sharing (SS) technologies towards 5G development and recent 5G-enabling technologies. SS techniques are classified, and SS surveys and related studies on SS techniques relevant to 5G networks are reviewed. The surveys and studies are categorised into one of the main SS techniques on the basis of network architecture, spectrum allocation behaviour and spectrum access method. Moreover, a detailed survey on cognitive radio (CR) technology in SS related to 5G implementation is performed. For a complete survey, discussions are conducted on the issues and challenges in the current implementation of SS and CR, and the means to support efficient 5G advancement are provided.

Generally, waste heat is redundantly released into the surrounding by anthropogenic activities without strategized planning. Consequently, urban heat islands and global warming chronically increases over time. Thermophotovoltaic (TPV) systems can be potentially deployed to harvest waste heat and recuperate energy to tackle this global issue with supplementary generation of electrical energy. This paper presents a critical review on two dominant types of semiconductor materials, namely gallium antimonide (GaSb) and indium gallium arsenide (InGaAs), as the potential candidates for TPV cells. The advantages and drawbacks of non-epitaxy and epitaxy growth methods are well-discussed based on different semiconductor materials. In addition, this paper critically examines and summarizes the electrical cell performance of TPV cells made of GaSb, InGaAs and other narrow bandgap semiconductor materials. The cell conversion efficiency improvement in terms of structural design and architectural optimization are also comprehensively analyzed and discussed. Lastly, the practical applications, current issues and challenges of TPV cells are critically reviewed and concluded with recommendations for future research. The highlighted insights of this review will contribute to the increase in effort towards development of future TPV systems with improved cell conversion efficiency.

Monitoring the condition of transformer oil is considered to be one of the preventive maintenance measures and it is very critical in ensuring the safety as well as optimal performance of the equipment. Various oil properties and contents in oil can be monitored such as acidity, furanic compounds and color. The current method is used to determine the color index (CI) of transformer oil produces an error of 0.5 in measurement, has high risk of human handling error, additional expense such as sampling and transportations, and limited samples can be measured per day due to safety and health reasons. Therefore, this work proposes the determination of CI of transformer oil using ultraviolet-to-visible (UV-Vis) spectroscopy. Results show a good correlation between the CI of transformer oil and the absorbance spectral responses of oils from 300 nm to 700 nm. Modeled equations were developed to relate the CI of the oil with the cutoff wavelength and absorbance, and with the area under the curve from 360 nm to 600 nm. These equations were verified with another set of oil samples. The equation that describes the relationship between cutoff wavelength, absorbance and CI of the oil shows higher accuracy with root mean square error (RMSE) of 0.1961.

Water can be an irritant to a power transformer, as it is recognized as a major hazard to the operation of transformers. The water content of a transformer insulation system comprises the water in the transformer insulation oil and in the cellulose paper. The increase in the water content in the insulation system leads to reduced breakdown voltage, accelerated aging of the oil–paper insulation system, and the possibility of producing bubbles at high temperatures. Therefore, various techniques have been applied to measure the water content in both oil and paper insulation. This article comprehensively reviews and analyzes the methods (technically or nontechnically) that have been used to monitor the water content in transformer insulation systems. Apart from discussing the advantages and major drawbacks of these methods, the accuracy, measurement time, and cost of each technique are also elucidated in this review. This review can be extremely useful to the utility in monitoring and maintaining the good condition of transformers. Based on the reviewed methods and their challenges, a few future research directions and prospects for determining the water content in transformer insulation systems are outlined, such as utilizing artificial intelligence and enhancing current techniques.

Power-over-fiber (PoF) is not a relatively new term in photonics and has been studied since the 1970s.¹ PoF, at its core, is a system in which a high-power laser source transmits a few watts of optical power on a single mode (SMF) or a multimode fiber (MMF). A photovoltaic (PV) converter converts the optical power into electrical power at the receiving end. The system has been studied in various applications such as Internet of Things (IoT),^{2 – 4} optical powering of remote antenna units,^{5 – 8} sensor monitoring systems,^4,5 submarines,^6,7 video camera systems,^8,9 and high voltage applications.^{10 – 12} PoF is also found to be a safer alternative in distributing power using optical fiber. Comparatively, copper wire possesses a much higher power transmission efficiency at more than 98% and it has the capacity of carrying high power, hence it is extensively used as a medium in transferring electrical power. However, optical fibers are preferable due to their robustness to electromagnetic interference (EMI), short circuit, and sparks.¹³ The fibers’ immunity to EMI is due to the fact that no radiation is emitted to cause an interference. Optical fibers are also less bulky, capable of operating over long distances, and impervious to moisture and corrosion.¹⁴

Periodic preventive maintenance of power transformer should be conducted for its health monitoring and early fault detection. Transformer oil is a vital element where its contents and properties need to be monitored during the service life of a power transformer. This paper presents an optical spectroscopy measurement from 200 nm to 3300 nm to characterize the transformer oil, which were sampled from the main tanks and ‘on-load tap changer’ of power transformers. The correlation of the optical characteristics in the range of 2120 nm to 2220 nm to the Dissolved Gas Analysis results and Duval Triangle interpretation demonstrates that the low energy electrical discharges, high energy electrical discharges as well as the thermal faults rated at temperatures above 700°C in power transformers can be accurately predicted. For faster and accurate analysis of fault prediction, a data mining analytics tool was constructed using Rapid Miner server to analyze and verify the predictions for a total of 108 oil samples. For the optimization, continuous iterations were performed to determine the best absorbance-wavelength combination that can improve the accuracy of the prediction. The performance of the optical spectroscopy technique integrated with data analytic tool was analyzed and it was found that the technique contributes to a high accuracy of 98.1% in fault prediction. It is a cost-effective and quicker complementing approach to carry out pre-screening of the transformer oil in order to know the condition of the power transformers based on the transformer oil’s optical characteristics.