Urban 5G NR Deployment: A Techno-Economic Case Study in Semarang

The article is devoted to a comprehensive analysis of key aspects of the development of fifth-generation (5G) networks in Ukraine. Current problems and prospects for the implementation of 5G are studied, taking into account technological, economic and regulatory aspects. Mathematical models and algorithms are proposed for optimizing the allocation of radio frequency spectrum, placement of base stations, implementation of virtualization of network functions Network Function Virtualization (NFV) and software-configured networks Software-Defined Networking (SDN), as well as ensuring quality of service (QoS) for different classes of traffic. The developed solutions allow to increase the efficiency of deployment and operation of 5G networks in conditions of limited resources. A mathematical model of spectrum allocation optimization using linear programming has been developed, which takes into account the efficiency of spectrum use by different operators. To optimize the placement of base stations, an approach based on game theory is proposed, which takes into account bandwidth limitations and placement costs while ensuring the necessary coverage. A mathematical model is presented for optimizing the placement of virtualized network functions on servers with limited resources in order to minimize costs and ensure the required performance. An algorithm based on gradient descent for dynamic resource management and QoS is proposed. Based on a comparative analysis of optimization methods, an integrated approach to solving key problems of 5G implementation is developed. A mathematical model for optimizing the allocation of radio frequency spectrum based on linear programming is proposed, which provides an increase in spectral efficiency by 23–27 % compared to basic methods. A game-theoretic approach to optimizing the placement of base stations is presented, which allows reducing the number of overloaded sectors by 45 % and increasing energy efficiency by 13.3 %. A genetic algorithm for optimizing the placement of virtualized network functions (VNF) is developed, which provides a 21.4 % higher resource utilization. Experimental studies have confirmed that the proposed solutions allow achieving an overall increase in network efficiency by 20–25 % while reducing operating costs by 15–20 %. The results create a methodological basis for effective planning and deployment of 5G networks in Ukraine.

5G is the fifth generation of wireless network technology and all the big carriers are working on building out their 5G networks. The main theme of 5G is speed, every new generation of the wireless networks are significantly faster and more capable than the previous and 5G is another step forward from 4G. 5G is built on what’s called a millimetre wave, it’s a new section of very high frequency spectrum upwards of 20 GHz all the way to near 96 GHz. The higher the frequency of any wave the lesser the range. To take advantage of 5G, you need a 5G device with appropriate antenna and a dense network of 5G base stations. This paper deals with the process of planning and deployment of 5G networks. The planning process will optimize the locations and minimize the number of base stations in a selected geographical area using a heuristic algorithm like genetic algorithm. Genetic algorithms help with efficient deployment of 5G networks by minimizing the search space for deployment of BS in area of interest. Multi Objective Genetic Algorithm (MOGA) incorporates multiple factors like cost, coverage, and interference in its fitness function in order to reach a global optimal solution for 5G deployment problem.

The Philippines is home to thousands of off grid islands that are too distant from the mainland and consequently expensive to connect to the main grid. These islands are typically powered by diesel generators, which will require more subsidies as fuel costs continue to increase. Hybrid renewable energy systems (HRES) are an alternative energy source with lower reliance on fuel and generation costs. In this work, the financial sustainability of deploying HRES in Philippine off grid islands of various sizes was evaluated. Patongong Island, Lapinigan Island, Balabac Island, and Sibuyan Island were selected as case studies as their peak electrical demand varies from 4.4 kW in Patongong Island to 3.2 MW in Sibuyan Island, representing a large fraction of off-grid islands in the country. HRES consisting of solar photovoltaics, wind turbines, lithium ion batteries, and diesel generators in these islands were modeled in Island Systems LCOEmin Algorithm (ISLA), an in house energy systems modeling tool. Profitability metrics, such as the net present value, internal rate of return (IRR), and payback period (PBP), were then calculated at varying electricity prices. The large Sibuyan island was already profitable at 0.2 USD/kWh, comparable to the mainland rate, which suggests that subsidies in large islands can be removed. The low 11 % IRR and 13 year PBP may not be attractive to private investors, but this may be alleviated by raising electricity prices. Other islands, however, will still require subsidies as the small Patongong Island becomes profitable only at 1.5 times the mainland rate. This work encourages private sector participation by providing financial insights absent in many techno economic studies. Moreover, this study enlightens the public sector about the necessity of subsidies for providing energy access in small off grid islands.

Solar power plants are expected to play a significant role in India’s power sector. The country plans to achieve an installed capacity of 100 GW by 2022. However, in a stand-alone mode, solar power plants are not able to deliver a consistent power supply, as per the demand requirement, to Electricity Supply Companies (ESCOMs). This is mainly because of the nature of intermittency associated with solar energy. Hybridization of renewable energy (RE) resources would significantly contribute toward solving this issue by providing a stable and sustainable supply. Biomass is a potential renewable resource for hybridization. Considering the technology maturity and economics, this study addresses solar photovoltaics and biomass hybrid systems for power generation and is restricted to decentralized applications. A detailed techno-economic case study has been presented for a 5-MW solar photovoltaic and biomass hybrid system in the present paper. At a capital cost of the hybrid plant at INR 10 crores/MW, the levelized cost of electricity (LCOE) and capacity utilization factor (CUF) for only solar (1-shift) are respectively INR 4.5/kWh and 10.7%. With sunshine hours in 1-shift mode in hybrid (both solar and biomass), the LCOE is INR 8.5/kWh and CUF is 24%, because the biomass system requires a higher capital investment (compared to solar) and less utilization (restricted to sunshine hours) for energy generation. If biomass system along with solar is utilized for 24 × 7 operation, the cost of generation reduces to INR 5.4/kWh (CUF 75%). However, PV-based hybrid plants with biomass system offer advantage only during the day time. The present results show that PV-biomass is a viable system and, more importantly, provides stable power to the grid during daytime without any battery support. Further, the biomass plant can be used to operate the plant beyond solar hours depending on the power demand and biomass availability.

Integration of pit thermal energy storages into district heating networks – a techno-economic case study

With the continuous maturity and application of 5G technology, the deployment and application of 5G network at sea have become an important research direction. In the marine environment, 5G wireless signal has unique propagation characteristics. This characteristic causes the poor adaptation of common channel propagation models and product parameter specifications. This paper analyzes the radio signal propagation characteristics of typical maritime communication scenarios, and compares 5G wireless signal transmission characteristics of different frequency bands. According to the characteristics and differences of NR technical solutions, an improved scheme is proposed to improve the design of base station side antenna and enhance the transmission power of terminal side. The simulation and experimental results show that the proposed scheme is reasonable and feasible. The 700MHz band and 5W terminal transmitting power are selected to meet the requirements of long-distance and large bandwidth network coverage for air and sea scenes.

In the upcoming era of 5G, the number of base stations, edge computing nodes and data centers is believed to be three to five times more than that of 4G. Serious challenges on the deployment and operation of 5G networks and services arise, especially on how to build and maintain battery energy storage systems for sustainable 5G power feeding at low cost for all scenarios. Although battery has long been used as a major backup power in various communications systems, current battery systems essentially are dumb devices. In the current battery systems, the charging/discharging energy flow is continuous due to the fixed series-parallel cell topology adopted by existing battery systems. The fixed topology also causes the bucket effect at the system level due to the fact that it is incapable of handling cell difference in a battery system, leading to a series of system-level problems in terms of power density, energy efficiency, cycle life, reliability, and safety. All these will make it very challenging for sustainable 5G power feeding, which will further affect the cost-effective deployment and operation of 5G networks and services. Thanks to the recent breakthrough of power electronics semiconductors, such as power metal-oxide- semiconductor field-effect transistor (MOSFET), silicon carbide (SiC) and gallium nitride (GaN) with their outstanding material properties, it becomes feasible to carry out digital energy processing operations at high switching speed, high voltage, and feverish temperature. By building a new digital grid-to-chip power train using high switching speed power semiconductors, traditional analog battery systems can be transformed into digital battery systems through energy digitization, which will significantly facilitate feasible 5G deployment and operation. In this article, we will propose and describe the basic concept of energy digitization, the design framework of the digital battery system including key components, modeling, and the performance evaluation of the digital battery system. Results of experiments and real-world applications show the effectiveness and efficiency of digital battery system, which offer a promising disruptive approach to sustainable 5G power feeding.

Indonesia has started the deployment of 5G networks to continue to develop in terms of telecommunications. However, accelerating the deployment of a 5G network will take a long time because the cost of deploying infrastructure is not cheap, and getting permits to build infrastructure in an area isn't easy. In 5G, it has a new business model, namely micro operators. Micro operators are 5G service deployments outside the deployment and Mobile Network Operators (MNO). Implementing micro operators can accelerate the deployment of 5G networks and connectivity distribution. With this approach, an analysis of the implementation of micro operators in Jababeka using the mmwave 28 GHz is carried out. From the results, there is an increase in the population. Scenario 1 shows a negative trend and scenario 3 show a positive trend. That means Indonesia can adopt scenario 3 to implement micro operator for the booster 5G network. In terms of regulation, Law Number 36 of 1999, Government Regulation Number 52 of 2000, Law Number 11 of 2020, and Government Regulation Number 46 of 2021 are the basis for discussing the proposed micro operator regulation based on existing rules in Indonesia.

The global deployment of 5G mobile networks has followed a progressive and strategic approach, depending on regional characteristics. This study develops a reference framework to prioritize areas for deployment, considering technical, sociodemographic, geographic, and economic criteria. The methodology integrates multi-criteria decision-making techniques such as AHP, CRITIC, TOPSIS, and SAW to evaluate and prioritize alternatives. This framework was applied to the municipalities of the Magdalena department in Colombia. The AHP results indicate that technical criteria are the most relevant in the selection process, with a weight of 34.3%, followed by sociodemographic criteria at 33.6%, geographic criteria at 19.47%, and economic criteria at 12.63%. A high similarity in municipality prioritization was observed, with a correlation of ρ = 0.9897 according to Spearman's coefficient. Using TOPSIS and SAW, the municipality of Ciénaga ranks first, given that the sub-criteria of population size, area, and 4G coverage hold the highest relevance in the selection process, with percentages of 13.13%, 12.16%, and 11.12%, respectively, while the municipalities of Fundación and Plato alternate between second and third place. On the other hand, La Zona Bananera ranks fourth and fifth. To assess the model's robustness against variability in the criterion weights, a sensitivity analysis was conducted using the Monte Carlo method with 10,000 iterations. The results indicate that the ranking remains stable, with an average correlation of ρ = 0.9010 between the rankings obtained with SAW and the final ranking using TOPSIS. The influence of high-weight and highly correlated sub-criteria was also assessed. Rankings from AHP-SAW and AHP-TOPSIS were compared with CRITIC-SAW and CRITIC-TOPSIS, yielding correlations of 0.98 and 0.76, respectively. It can be concluded that the deployment of 5G networks can be systematically prioritized based on the mentioned criteria, using a model that remains stable despite changes in criterion weights.

A continuing growth in the demand for faster cellular networks is driving the development of the forthcoming fifth generation of wireless networks, namely 5G. In comparison to previous generations of cellular networks, 5G networks have higher data-transfer rates, with low latency. However, increasing the data-transfer rate requires using high-frequency transmissions, which are susceptible to interference by obstacles like buildings and trees. Deployment of 5G networks, especially in urban areas, must take such obstacles into account when installing new antennas. It is required to carefully select antenna locations, in order to guarantee high coverage and reliability of the cellular network.

Media convergence is not a new concept in journalism studies, though available evidence indicates that convergence studies have been explored more in the global north than the global south. This study, contextualised in Nigeria, joins the media convergence conversation by exploring the sustainability of Facebook-radio convergence for distributing broadcast programmes by seventeen (17) licenced radio stations in Oyo State, Nigeria. As a computational content analysis study, researchers analysed 85 purposively selected programmes of the stations as broadcast live on their Facebook pages alongside the 9527 likes, 10,314 shares, 7007 comments and 170,681 views the programmes generated. Stakeholders’ interviews were also conducted for a broadcasting expert, presenters of some of the stations, together with audience of the selected stations. The main finding shows that programmes that focussed more on socioeconomic problems and opportunities, and were broadcast in the afternoon, evening and at night received more digital engagement than other programmes’ formats and time belts. Although high cost of Internet data subscription in the country, absence of Internet-enabled mobile phones among many adherents of radio programmes (both in rural and urban areas), epileptic power supply that sometimes leave many people with unpowered mobile phones as well as weak Internet broadband connectivity common to many locations in Nigeria threaten the sustainability of Facebook-radio broadcasting in Oyo State. Deployment of 5G network, installation of more network masts with strong bandwidth and training of radio presenters and radio stations' social media handlers on innovative and audience-participatory programme production are recommended.

This paper presents a novel method for incorporating the seasonal variations in gas demand into an assessment of the economic viability of a biomethane production and injection facility. A simulation of a gas distribution (Dx) network was built to investigate the impact of limits imposed by the gas network operator on the quantity of biomethane that can be injected. The results calculated the grid’s capacity to accept biomethane on an hourly basis over the course of a year. Scenarios of maximum, minimum and no demand at a Dx-connected compressed natural gas (CNG) filling station were computed for the 3 potential locations being investigated for the biomethane production and injection facility. This data was then used to determine a range of possible plant sizes for each potential facility location and CNG demand scenario. Next, a spatially explicit geographical information systems (GIS) model was created to map the distribution of feedstock suitable for biomethane production in the surrounding area and determine transportation distances. These two submodels fed into a techno-economic model that calculates the net present value (NPV) and levelised cost of energy (LCOE) for each configuration. Notably, the profitability of the plant was seen to increase proportionally with an increase in demand at the CNG filling station. Location 2 was determined to be the most economically viable site for the biomethane production and injection facility. The most economically competitive configurations resulted in an LCOE of 81.63 €/MWh, 83.59 €/MWh, and 83.73 €/MWh, with corresponding NPVs of M€ 9.56, M€ 3.98 and M€ 0.94, for maximum, minimum and no demand at the CNG filling station respectively. The most competitive configurations are achieved at a plant size of 115 GWh/a for the maximum CNG demand, 82.2 GWh/a for the minimum CNG demand, and 81.8 GWh/a for no CNG demand replacing 40%, 34%, and 35% of annual natural gas demand in the Dx network respectively.

This study compared the performance of supercritical water gasification (SCWG) to conventional anaerobic digestion (AD) for treating sewage sludge from a wastewater treatment plant (WWTP). Based on plant data from a WWTP in Norway, kinetic-based process models have been developed in Aspen Plus® to investigate the energy and economic feasibility of AD and SCWG for sewage sludge (SS) treatment. The findings showed that low ambient temperatures significantly reduced the energy efficiency of the AD, while their effect on the SCWG process was negligible. At the average ambient temperature of 7 °C and SS concentration of 7 wt%, AD and SCWG achieved thermal energy self-sufficiency (TES) of 0.76 and 0.63, respectively. Under these conditions, the AD and SCWG had energy conversion efficiencies (η) of 25.8% and 46.6%, respectively. However, increasing the SS content in the SCWG to 15 wt% improved the TES to 1.22 and η to 73.2%, making it a more attractive alternative to the AD.At 7 wt% SS concentration, the AD and SCWG processes required an investment cost of $ 4.08 million and $ 6.83 million, respectively. Under the study assumptions, neither AD nor SCWG proved profitable, revealing negative net present values (NPV) and operating costs of $0.96 million and $0.92 million, respectively.

The rapid evolution and deployment of 5G networks have introduced complex security challenges due to their reliance on dynamic network slicing, ultra-low latency communication, decentralized architectures, and highly diverse use cases. Traditional perimeter-based security models are no longer sufficient in these highly fluid and distributed environments. In response to these limitations, this study introduces SecureChain-ZT, a novel Adaptive Zero Trust Policy Framework (AZTPF) that addresses emerging threats by integrating intelligent access control, real-time monitoring, and decentralized authentication mechanisms. SecureChain-ZT advances conventional Zero Trust Architecture (ZTA) by leveraging machine learning, reinforcement learning, and blockchain technologies to achieve autonomous policy enforcement and threat mitigation. Unlike static ZT models that depend on predefined rule sets, AZTPF continuously evaluates user and device behavior in real time, detects anomalies through AI-powered traffic analysis, and dynamically updates access policies based on contextual risk assessments. Comprehensive simulations and experiments demonstrate the robustness of the framework. SecureChain-ZT achieves an authentication accuracy of 97.8% and reduces unauthorized access attempts from 17.5% to just 2.2%. Its advanced detection capabilities achieve a threat detection accuracy of 99.3% and block 95.6% of attempted cyber intrusions. The implementation of blockchain-based identity verification reduces spoofing incidents by 97%, while microsegmentation limits lateral movement attacks by 75%. The proposed SecureChain-ZT model achieved an authentication accuracy of 98.6%, reduced false acceptance and rejection rates to 1.2% and 0.2% respectively, and improved policy update time to 180 ms. Compared to traditional models, the overall latency was reduced by 62.6%, and threat detection accuracy increased to 99.3%. These results highlight the model’s effectiveness in both cybersecurity enhancement and real-time service responsiveness. This research contributes to the advancement of Zero Trust security models by presenting a scalable, resilient, and adaptive policy enforcement framework that aligns with the demands of next-generation 5G infrastructures. The proposed SecureChain-ZT model not only enhances cybersecurity but also ensures service reliability and responsiveness in complex and mission-critical environments.

Energy efficiency (EE) constitutes a key target in the deployment of 5G networks, especially due to the increased densification and heterogeneity. In this paper, a Deep Q-Network (DQN) based power control scheme is proposed for improving the system-level EE of two-tier 5G heterogeneous and multi-channel cells. The algorithm aims to maximize the EE of the system by regulating the transmission power of the downlink channels and reconfiguring the user association scheme. To efficiently solve the EE problem, a DQN-based method is established, properly modified to ensure adequate QoS of each user (via defining a demand-driven rewarding system) and near-optimal power adjustment in each transmission link. To directly compare different DQN-based approaches, a centralized (C-DQN), a multi-agent (MA-DQN) and a transfer learning-based (T-DQN) method are deployed to address whether their applicability is beneficial in the 5G HetNets. Results confirmed that DQN-assisted actions could offer enhanced network-wide EE performance, as they balance the trade-off between the power consumption and achieved throughput (in Mbps/Watt). Excessive performance was observed for the MA-DQN approach (>5 Mbps/Watt), since the decentralized learning supports low-dimensional agents to be coordinated with each other through global rewards. In further comparing the T-DQN against MA-DQN solutions, T-DQN presents beneficial usage for very low or very high inter-cell distances, whereas the usage of MA-DQN is preferred (by a factor of ~1.3) for intermediate inter-cell distances (100-600m), where the power savings are feasible towards achieving increased EE. Furthermore, T-DQN scheme guarantees good EE solutions (above 2 Mbps/Watt), even for densely-deployed macro-cells, with effortless training and memory requirements. On the contrary, MA-DQN offers the best EE solutions at the expense of massive training resources and required training time.