The next generation 5G radio access network (RAN) system is believed to be a true world wide wireless web (WWWW). This is because such system will seamlessly and ubiquitously connect everything, and support at least 1000-fold traffic volumes, 100 billion connected wireless devices, and diversified use cases as well as quality of service (QoS) requirements (e.g., reliability, latency, data rates, coverage, security, and privacy) of multimedia applications by 2020. Recently, a number of research challenges including the explosive growth in mobile traffic volumes, unprecedented connected devices, and diversified use cases have been identified for the 5G RAN systems. In addition, specific technologies such as multitier communication, massive MIMOs, mmWave backhauling, extreme densifications of nodes (UDNs), full-duplex communications (FDCs), and energy harvesting techniques have emerged in the literature to resolve some of these challenges of the 5G RAN systems. However, the research activities defining specific technical advancements for 5G RAN systems are yet to continue in the next half decade before specifications for standardization and commercialization are concluded. Motivated by the limited number of existing surveys of such technical advancements in a broader perspective (i.e., interference, spectrum-efficient, and energy-efficient management schemes), this paper seeks to take stock of state-of-the-art (SOTA) on such technical developments. Our attention focuses on relevant radio interference and resource management (RIRM) schemes that have been proposed in the last five years. Our contribution lies in the analysis, synthesis, and summarized alignments of the conventional RIRM schemes toward overcoming the identified challenges for the 5G RAN systems. Finally, the review highlights a number of open research issues deduced from recently proposed RIRM schemes.

Globally, groundwater is the largest distributed storage of freshwater and plays an important role in an ecosystem’s sustainability in addition to aiding human adaptation to both climatic change and variability. However, groundwater resources are dynamic and often change as a result of land usage, abstraction, as well as variation in climate. To solve these challenges, many conventional solutions, such as certain numerical techniques, have been proffered for groundwater modelling. The global evolution of the Internet of Things (IoT) has enhanced the culture of data gathering for the management of groundwater resources. In addition, efficient data-driven groundwater resource management relies hugely on information relating to changes in groundwater resources as well as their availability. At the moment, some studies in the literature reveal that groundwater managers lack an efficient and real-time groundwater management system which is needed to gather the required data. Additionally, the literature reveals that the existing methods of collecting data lack the required efficiency to meet computational model requirements and meet management objectives. Unlike previous surveys, which solely focussed on particular groundwater issues related to simulation and optimisation management methods, this paper seeks to highlight the current groundwater management models as well as the IoT contributions.

The sustainability of a clean energy transition for electric vehicle transportation is clearly affected by increased energy consumption cost, which is associated with large-scale electric vehicles (EVs) charging on a fossil-fuel dependent electricity grid. This places a potential threat on the safe operations and stability of the grid and increases the emissions of greenhouse gases (GHGs) from the power stations that generate the electricity. Furthermore, the uncontrolled large-scale integration of EVs charging on the grid will increase exponentially in the coming years. Because of this, new peaks on the grid will be generated due to the EV charging load variance, and a significant impact on the transformer limit and substation capacity violation will occur. To mitigate the significant impact of the high cost of energy consumption by large-scale EVs charging on the grid, and to reduce the emissions of GHGs, there is a need to provide a multi-level optimization approach that is robust and dynamic to solve the uncontrolled charging problem of large-scale integration of EVs to the grid. This paper investigates the grid energy consumption by EVs and reviews recent applications of EV charging controls and optimization approaches used for the energy management of large-scale EVs charging on the grid. Energy management in this context is not trivial. It implies that the objectives such as load shifting, peak shaving, and minimizing the high cost of electricity consumption with a stable grid operation can be achieved. In the context of this study, EVs charging on the grid includes both battery electric vehicles (BEVs), which have larger battery banks with a longer charging duration and higher energy consumption capacity, and plug-in hybrid electric vehicles (PHEVs) which have smaller battery capacities.

Over the years, sustainability and impact on the environment, as well as operation expenditure, have been major concerns in the deployment of mobile cellular base stations (BSs) worldwide. This is because mobile cellular BSs are known to consume a high percentage of power within the mobile cellular network. Such energy consumption contributes to the emission of greenhouse gases (GHGs) through the use of conventional diesel generating set (gen-set). As a result, mobile cellular operators are faced with the dilemma of minimizing the power consumption, GHG emissions, and operation cost, while improving the quality of service (QoS) of the networks. In attempting to find a solution, this study presents the feasibility and simulation of a solar photovoltaic (PV)/battery hybrid power system (HPS), as a predominant source of power for a specific mobile cellular BS site situated in the Soshanguve area of the city of Pretoria, South Africa. It also presents the technical development and shows the environmental advantage and cost benefits of using a solar PV/battery HPS to power a BS site with a 24 h daily load of 241.10 kWh/d and peak load of 20.31 kW as compared to using the HPS with a solar PV/diesel gen-set/battery. The solar resource pattern for the city of Pretoria was collected from the National Aeronautics and Space Administration and was modeled statistically. The statistical modeling done using solar radiation resource exposure characteristic patterns of Pretoria, South Africa revealed an average annual daily solar radiation of 5.4645 Wh/m²/d and a 0.605 clearness index. The simulation and the design were done using Hybrid Optimization Model for Electric Renewables (HOMER) and Matlab/Simulink software. The simulation finding showed that the HPS of the solar PV/battery combination has about a 59.62% saving in the net present cost (NPC) and levelized cost of energy (LCOE) and an 80.87% saving in operating cost as against conventional BSs powered with a gen-set/battery.