Cost–Benefit Assessment of 5G Rollout: Insights from Brazil

Abstract

This study provides a comprehensive techno-economic evaluation of the implementation of the 5G network, focusing on the southern region of Brazil. The research examines the capital expenditure (CAPEX) and operational expenditure (OPEX) associated with 5G deployment, assessing the economic viability of various deployment strategies. By analyzing international practices, such as sharing infrastructure, cutting networks, and using neutral networks, this study presents a detailed cost analysis and proposes models to optimize investment. A comparative evaluation of deployment costs between the southern region of Brazil and Belgium underscores the need to adapt European cost models to the Brazilian context. In addition, a case study on rural areas in southern Brazil identifies key challenges and opportunities, highlighting the unique aspects of the implementation of 5G in these regions. This study offers insights into optimizing investments in 5G networks, with the objective of supporting informed decision making for network expansion in diverse geographical and economic contexts.

1. Introduction

The viability of exploiting higher-frequency radio waves via 5G marks a significant transformation in the telecommunications landscape, promising increased capacity and speed of existing connectivity, in addition to enabling a range of new applications and services. Given the multitude of possibilities, it becomes essential to conduct a robust assessment of the economic performance of competing engineering systems. The role of the techno-economic assessment (TEA) is central in this context, providing a quantitative methodology that allows for the evaluation of such performances in monetary terms. Assessing cost structures and revenue projections is crucial to facilitate informed decision making regarding the development and implementation of new technologies.

The TEA adopts a holistic approach to the process, evaluating potential externalities beyond direct and indirect costs, such as the environmental impact, data transmission efficiency, and coverage reach. This multidimensional approach provides a robust framework for assessing the economic and technological impacts of the evaluated structures.

From a cost perspective, the methodology proposes modeling by distinguishing between capital expenditure (CAPEX) and operational expenditure (OPEX), aggregating them as the total cost of ownership (TCO). TCO analysis offers a comprehensive perspective on the economic impact over time, allowing for a more accurate assessment of the feasibility and economic sustainability of emerging technologies.

This paper focuses on the cost analysis and economic viability of implementing 5G networks, particularly focusing on the Brazilian scenario. By reviewing significant international studies and practices, this work aims to establish a solid framework for cost modeling and compare the economic feasibility of various deployment strategies. The objectives include quantifying the CAPEX and OPEX costs associated with the implementation and long-term operation of 5G.

To provide a comprehensive perspective, this study examines 5G deployment practices in various countries, including the United States, India, Europe, and Latin America. In the United States, the leadership in 5G technology is characterized by pioneering approaches and significant contributions to network development. India’s vast territory and diverse socioeconomic conditions offer a relevant comparison for Brazil, providing insights into 5G strategies in emerging markets. Latin American countries, which share similar challenges regarding extensive rural areas and diverse geographic conditions, are also considered. Furthermore, this study evaluates 5G infrastructure sharing models in rural European regions, highlighting various strategies and their techno-economic implications.

In the Brazilian context, this study focuses on specific aspects of the implementation of 5G technology. Initially, the application of 5G in remote areas is analyzed, highlighting the challenges faced and the opportunities to promote digital inclusion in these regions. A case study of the southern region of Brazil is conducted to analyze local challenges and opportunities in 5G deployment, providing a focused examination of regional dynamics and their impact on the feasibility of 5G networks.

By highlighting these comparisons and drawing insights from international practices, this article aims to contribute significantly to the ongoing discourse on the development and deployment of 5G networks in Brazil. The goal is to inform stakeholders in the telecommunications sector and improve the analysis of cost structures to support the sustainable implementation of this new technology.

While numerous techno-economic studies have explored 5G deployment in Europe, North America, and parts of Asia, there remains a gap in the literature concerning Latin America, particularly in assessing the cost structures and regulatory challenges of rural deployment. This study contributes to bridging that gap by conducting a region-specific CAPEX and OPEX assessment in the southern region of Brazil, a representative area that combines rural and urban typologies. Furthermore, by critically comparing cost structures with European models and evaluating the relevance of strategies such as infrastructure sharing and network slicing, this work provides novel insights for adapting global practices to Brazil’s regulatory and geographic conditions. To our knowledge, this is one of the first techno-economic analyses to apply this combined approach in the Latin American context.

This study is organized as follows: Section 2 provides the theoretical framework and includes a comprehensive analysis of the capital and operational expenditures associated with the deployment and maintenance of the 5G network. Section 3 discusses selected international practices, highlighting different strategies for 5G implementation. Section 4 presents a case study on southern Brazil, illustrating the challenges and opportunities of 5G deployment in the region. Finally, Section 5 concludes this study, summarizing the findings and offering recommendations.

2. Technical Enablers and Related Work

The deployment and cost structure of 5G networks are strongly influenced by a set of enabling technologies that underpin its architecture and scalability. Among these, Massive MIMO (multiple-input multiple-output), small cells, heterogeneous networks (HetNets), and network slicing stand out as critical components. Each contributes to the improvement of spectral efficiency, latency, coverage, and service differentiation. Understanding these technical enablers is essential for techno-economic modeling, as they shape both capital expenditures and operational expenditures, as well as the range of vertical applications and service opportunities that 5G supports. During the first four generations of cellular technologies, up to 4G in 2010, mobile network operators (MNOs) relied on selling subscriptions based on voice and data consumption. However, the surge in mobile data demand and the widespread adoption of unlimited data plans posed challenges to sustaining revenue growth, prompting the exploration of new opportunities through 5G services. Thus, 5G offers MNOs the potential to diversify into areas such as private networks, massive IoT, and ultra-reliable low-latency communications, generating new revenue streams [1].

MNOs are now applying 5G in various sectors, or “verticals”, including energy, healthcare, manufacturing, agriculture, and transportation. This shift requires sector-specific adaptations in software, hardware, and the spectrum [2]. The success of 5G depends on both technical and economic viability, requiring detailed techno-economic assessments to determine deployment costs and potential value. Although 5G supports three main use cases, namely enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), and ultra-reliable low-latency communication (uRLLC), only eMBB has achieved widespread commercial success so far [3].

eMBB builds on 4G, offering higher data rates and spectral efficiency, making it the first phase of 5G deployment [4]. It utilizes the 5G New Radio (5GNR) and 4G Evolved Packet Core (EPC), proving its economic viability for MNOs. However, mMTC, mainly related to the Internet of Things (IoT), faces challenges due to market fragmentation, while uRLLC, which is designed for high-reliability and low-latency applications, requires further advancements in 3GPP standards [5].

The technical design of 5G benefits from various innovations in research and development (R&D). Network capacity can be expanded by increasing cell density, adding spectrum bandwidth, and improving spectral efficiency. Small cells and HetNet increase capacity, while the millimeter-wave spectrum and the 3.5 GHz band expand the available frequencies [6].

Notably, Massive MIMO radio technology represents a significant advancement for spectral efficiency. This technology utilizes multiple antennas on base stations and mobile devices to transmit and receive more data simultaneously [7]. With Massive MIMO, it is possible to precisely manipulate signal beams, directing them to specific users and reducing interference. This not only improves service quality but also increases network capacity, making it one of the most crucial tools in the 5G arsenal to address the growing demand for high-speed data and services [8].

However, 5G is not a single technology but a series of options that allow MNOs to adapt the network to their needs and implementation stage. Among the various possible options, standalone (SA), non-standalone (NSA), and the architectures proposed by the 3rd Generation Partnership Project (3GPP) stand out. Each option has technical advantages and disadvantages and a different implementation cost [3].

Considering this, the cost estimation of the electromagnetic spectrum for wireless communication is a multidisciplinary problem that involves a complex interplay of various fields such as engineering, economics, policy and regulation, computer science, business, social sciences, environmental sciences, mathematics, and physics. This work discusses cost estimation by comparing the methodologies used in different countries.

Costs Analysis

In the past, TEA used spreadsheets for modeling. However, currently software-based methods are preferred due to their flexibility and precision, especially with advanced techniques such as sensitivity analysis and Monte Carlo simulations [9]. Economic analysis involves modeling production costs and potential demand for the goods and services evaluated. Production costs are generally analyzed by combining capital and operational expenses, providing a comprehensive view of the TCO throughout the life cycle of the asset [7].

Discounted cash flow (DCF) analysis is based on the principle that funds available in the present are more valuable than the same amount in the future due to the potential for earnings. Therefore, future cash flows are discounted to reflect this present value by using a discount rate that typically corresponds to the weighted average cost of capital (WACC). These costs can then be related to potential revenue streams from the demand side, providing simultaneous insights into the net present value (NPV), return on investment (RoI), and internal rate of return (IRR) [3].

According to [10], the techno-economic assessment process follows three main steps. In the first step, engineering designs representing different cellular technologies are defined. Many analyses focus on modeling the capacity and coverage of a cellular system for various levels of service quality. For example, these assessments can focus on the spectral efficiency of a technology, the available bandwidth for an operator, the cell density of existing sites, and the level of sectorization. Some studies also consider energy consumption by quantifying the electricity usage of specific technologies [11].

In the second step, the resources needed to achieve the level of service quality established in the first step are quantified. This includes evaluating network components such as towers, antennas, and other essential equipment, as well as calculating the quantity of each item required to build and maintain the network [3]. In the third step, a set of corporate finance techniques is applied to assess the capital and operational expenditures necessary to build and operate a wireless network. TCO is ideally used to capture the range of CAPEX and OPEX payments incurred over the asset’s and network’s lifecycle.

CAPEX refers to the investments needed to establish the network, including acquiring essential equipment, building network infrastructure, installing base stations, and acquiring the spectrum. These costs are typically incurred at the project’s outset and capitalized on the company’s balance sheet, being amortized over time. CAPEX is crucial for the planning phase as it represents the amount of financial resources that need to be allocated to build the physical infrastructure required for network operation.

However, OPEX encompasses the recurring costs associated with managing and maintaining the telecommunications network. This includes expenses for equipment maintenance, the rental of sites for technical installations, energy consumption to operate the infrastructure, and the salaries of employees involved in network operation and maintenance. Unlike CAPEX, OPEX reflects the ongoing cost of operating and maintaining the network, directly affecting the company’s operational profitability.

3. 5G International Practices

This section examines the various strategies and practices adopted by various countries in deploying 5G networks, providing a comparative analysis of their techno-economic implications. By evaluating the approaches of key nations, we aim to identify best practices, challenges, and innovative solutions that can inform future 5G implementations globally. The selected countries represent a mix of developed and emerging markets, offering a comprehensive view of the deployment of 5G in different economic and infrastructure contexts.

Among the main practices observed, the MIMO structure, characterized by the simultaneous transmission of signals, stands out. This structure allows a single unit to receive signals simultaneously from multiple transmitters and distribute them in a dispersed manner. Another relevant practice is the capability of transmission in millimeter waves (mmWaves). These waves are characterized by extremely high frequencies and are measured in millimeters because of their short wavelengths.

Finally, each component of the transmission network can have different characteristics, ranging from the physical arrangement of the components to security protocols and operating systems. These particularities of each network element characterize a heterogeneous data transmission network. The possibility of applying a heterogeneous network allows participants to employ specific solutions for different scenarios encountered during the implementation of a network structure that supports signal transmission.

3.1. United States of America

The study by [12] focuses on a techno-economic evaluation of 5G deployment in Texas, United States, particularly addressing the use of Massive MIMO HetNets over mmWaves at the 28 GHz frequency. The main objective is to assess the financial viability of different deployment scenarios, particularly in heterogeneous networks with varying population densities. Two primary deployment models are considered: Dense Urban and Macro-Urban.

In the Dense Urban scenario, the focus is on areas with high population density and significant data traffic, such as city centers and commercial districts. The deployment strategy incorporates macro- and micro-cells to manage the high demand, especially for indoor coverage, where signal penetration can be challenging. This scenario aims to provide robust coverage and high data transfer rates in areas of intense demand, such as large office buildings, shopping centers, and entertainment areas. The financial analysis of this scenario shows a positive net present value (NPV) of USD 482.1 million and a modified internal rate of return (MIRR) of 11%, indicating strong profitability and potential for investment.

On the other hand, the Macro-Urban scenario is designed for larger urban and suburban areas, where the population density is lower but the need for continuous coverage remains high. This scenario uses long-range cells to minimize the number of base stations needed, reducing overall infrastructure costs. However, the financial outlook for this scenario is less favorable. The analysis reveals a negative NPV of −USD 2.56 billion and a MIRR of −12%, indicating that, under current conditions, this deployment model would not be profitable. A negative financial performance suggests that this scenario involves higher risks and may not generate sufficient returns to justify the investment.

The comparison between these two deployment scenarios highlights the critical role of detailed financial analysis in planning 5G network deployments. Although the Dense Urban scenario emerges as a financially viable and promising investment, the Macro-Urban model presents significant financial challenges, requiring further considerations to mitigate risks and improve profitability.

The negative financial outcome observed in the suburban scenario, despite lower infrastructure investments, can be attributed to several interrelated factors. First, suburban areas often experience more dispersed user distribution, which reduces the average revenue per site compared to dense urban environments. While users in both urban and suburban areas engage in data-intensive activities such as streaming and social networking, suburban users are more likely to connect through home Wi-Fi networks, reducing reliance on mobile data. Additionally, the temporal pattern of network usage may differ: urban areas tend to concentrate high traffic volumes during working hours, whereas the suburban demand peaks later in the day, potentially resulting in the underutilization of infrastructure during large portions of the day. These factors combined diminish the potential return on investment in suburban zones, thereby contributing to the observed negative NPV in the techno-economic analysis of the Texas case study [12].

3.2. India

The study by [13] focuses on the implementation of 5G through the neutral host network (NHN) model in rural India, using network slicing to enhance connectivity. Given India’s geographical diversity, which includes mountains, plains, and deserts, providing reliable Internet in rural regions, where about 70% of the population resides, presents significant challenges. The goal is to address the digital divide by offering an economically sustainable solution for 5G deployment in areas where connectivity is limited.

The study evaluates different deployment scenarios using simulations and cost modeling to estimate capital expenditures and operational expenditures. CAPEX includes the costs of establishing the infrastructure, such as base stations, fiber optics, and backup systems, while OPEX covers recurring costs, such as maintenance, site rentals, and spectrum fees. By optimizing these costs, the NHN model allows different service providers to share the same physical infrastructure, significantly reducing the investment required for 5G deployment in rural areas.

Network slicing, a key component of this model, segments the 5G infrastructure into virtual slices, each serving different tenants or applications. This segmentation ensures that each slice operates independently, offering customized bandwidth, latency, and security configurations to meet specific customer needs. For example, a rural healthcare service may require low-latency, high-reliability connectivity, while agricultural monitoring might prioritize broader coverage with lower bandwidth.

The NHN model also relies on a neutral infrastructure provider (InP), which manages the network without offering services directly. The InP ensures that multiple service providers can operate using the same network infrastructure, maximizing efficiency and versatility. This model can reduce CAPEX and OPEX while maintaining high service quality, making the implementation of 5G more viable in rural areas.

In terms of economic feasibility, the study highlights that regions with lower population densities, such as Dhanushkodi, require more aggressive pricing strategies to be sustainable. However, areas with higher population densities, such as Bandholi and Muddunoor, demonstrate stronger economic viability due to higher demand and easier access to revenue streams.

3.3. Europe

The study by [14] performs a techno-economic evaluation of 5G infrastructure sharing models in rural Europe, focusing on different approaches such as the single-host network (SHN), the multiple-host network (MHN), and the NHN. The goal is to assess the costs, returns, and feasibility of these models by analyzing capital expenditures, operational expenditures, and key financial metrics such as the net present value (NPV) and return on investment (ROI). The study highlights the importance of population density in determining the success of these models.

The analysis groups European countries into five categories based on the density of the rural population and settlement patterns. It examines two types of areas: rural settlement areas, which require substantial data capacity, and non-residential rural areas, where the priority is providing mobile coverage. The NHN model, where a single infrastructure provider manages the network, incurs higher total costs due to the extensive coverage and higher density management. However, this model also benefits from shorter payback periods and a higher NPV in densely populated areas thanks to the revenue generated from wholesale agreements through network slicing.

In contrast, less collaborative models, such as no sharing (NS) and passive site sharing (PSS), have longer payback periods, especially in sparsely populated areas, making them less economically viable in rural regions. The study suggests that the NHN is the most cost-efficient model for rural deployments due to its ability to spread costs over multiple service providers, resulting in greater economic benefits and a higher ROI, particularly in densely populated areas.

Sensitivity analysis shows that factors such as average revenue Per user (ARPU) and projected demand levels significantly affect investment viability. The NHN model, in particular, benefits from the ability to charge for wholesale access, which boosts its profitability. However, it also carries the risk of creating monopolies in rural areas, which would require regulatory interventions.

In general, the study concludes that deeper infrastructure sharing models such as the NHN and MORAN provide the best financial results for rural 5G deployment, while less collaborative models are less attractive due to higher costs and lower returns.

4. Case Study in Southern Brazil

In 2021, Brazil held a multiband auction for 5G technology, offering the spectrum in the 700 MHz, 2.3 GHz, 3.5 GHz, and 26 GHz bands, totaling 3710 MHz auctions in the event held in November [15]. The reserve price set by the regulatory body was BRL 10.6 billion (USD 2.03 billion), with a right concession period of 20 years. In this context, the unit costs of the equipment and support infrastructure were obtained through data requests from manufacturers and high-speed broadband service providers, as well as from Anatel’s bottom-up cost model. For a more precise understanding of the approach used in pricing base stations (BSs), network elements were classified into three main categories: (i) civil infrastructure (towers); (ii) the BS, which includes the set of equipment comprising the control, transmission, and radiating systems; and (iii) backhaul, which comprises the transport elements from the LTE site to the provider’s network.

The costs of BSs include the entire set of equipment necessary for the operation of the control, transmission, and radiating systems. These values are based on the unit CAPEX estimates provided by the Anatel Bottom-Up Cost Model, reflecting a realistic and detailed view of the required investments. Figure 1 shows the percentage of the final values considered for CAPEX and OPEX:

The analysis of the CAPEX data reveals that the largest portion of the investments was allocated to tower infrastructure, representing 48.32% of the total. These findings underscore the importance of physical infrastructure in the deployment of 5G networks. The percentage values presented in Figure 1 and Figure 2 were obtained from Anatel’s official cost modeling documentation and data requests submitted to local broadband service providers. Specifically, CAPEX and OPEX figures were derived from Anatel’s Bottom-Up Cost Model [15], while the regional typology data used in Figure 2 are based on IBGE’s rural–urban classification [16].

Radio equipment, which accounts for 19. 70% of CAPEX, constitutes the second largest component of CAPEX, reflecting the costs associated with the devices necessary for signal transmission and reception. Energy accounts for a considerable portion, at 15.19%, followed by fiber optics (12.91%), which is crucial to ensure high transmission capacity. Backhaul microwaves and residential CPE represent smaller portions, 2.64 and 1. 23%, respectively, indicating that, although important, they are not the primary cost components. Regarding OPEX, the most significant cost is associated with tower rental, which constitutes 54.05% of the total. These data confirm the strategic importance of using existing towers to minimize operational costs.

The costs associated with the operation and maintenance of radio equipment, which account for 19.05% of the total costs, highlight the need for the continuous maintenance of these devices. Energy remains a relevant factor, representing 12.21% of OPEX, followed by backhaul microwaves at 11.97%. Fiber optics has a smaller impact on OPEX, with only 2.71%, which can be attributed to the efficiency and robustness of the fiber infrastructure in terms of maintenance and operation.

Comprising the states of Paraná (PR), Santa Catarina (SC), and Rio Grande do Sul (RS), the southern region of Brazil was chosen for this case study because it is the smallest of the five major Brazilian regions in terms of area and population. This characteristic facilitates data collection and analysis, providing a clear and detailed view of the challenges and opportunities in the deployment of 5G technologies. In addition, the southern region combines urban and rural characteristics, offering a diverse scenario representative of other parts of Brazil. Although these results provide valuable information on 5G implementation in the studied region, they may not be fully applicable to all geographic and demographic contexts in Brazil, such as the Amazon region. However, they offer an important starting point for understanding deployment strategies in specific areas, paving the way for further studies in other regions with different challenges.

The typology of the southern region of Brazil, as classified by the Brazilian Institute of Geography and Statistics (IBGE), divides the region into intermediary, rural, and urban areas. According to data, 64.65% of the southern region is classified as rural, 26.20% as urban, and 9.15% as intermediary (Figure 2). Considering that the rural population represents approximately two thirds of the southern region, the population density in these areas is particularly relevant.

Using IBGE data [16], a rural population of 4,879,574 was estimated to have been spread over an area of 576.774 km². This results in a density of rural population of approximately 8.46 inhabitants per km². This density figure is significant because it reflects the dispersed nature of the rural population, which has implications for strategic planning and the implementation of telecommunication infrastructures, particularly to ensure efficient coverage in low-density areas.

The density of the rural population, calculated at approximately 8.46 inhabitants per km², aligns closely with the density of the rural population observed in Belgium (8 pop/km²), as discussed in the study by [14]. As Group 5 of the study, Belgium shares similar rural density characteristics, making it a pertinent reference point for evaluating cost structures. Therefore, while the cost structure used in Belgium provides useful reference points, it is important to recognize that this study applies only unitary equipment costs and does not account for other factors specific to the telecommunications sector that could impact mobile network deployment in Brazil. As such, any direct comparison or application of Belgium’s cost structure to regions like southern Brazil would require further, more comprehensive analysis.

The comparative analysis reveals significant differences in the cost structures between Belgium and Brazil (Figure 3). In Belgium, towers constitute 23.00% of all buildings, radio equipment 49.00%, backhaul 9.00%, and residential CPE 4.00%. In contrast, in Brazil, towers accounted for 48.32%, radio equipment for 12.91%, backhaul for 34.89%, and residential CPE for 1.23%. These discrepancies demonstrate that European cost models are not directly applicable to Brazil without a broader evaluation. A detailed assessment of the telecommunications sector is required to determine how these models could be tailored to address Brazil’s specific geographic, economic, and regulatory challenges. The higher costs of the towers in Brazil suggest a greater dependence on physical infrastructure. In contrast, lower costs for radio equipment and residential CPE indicate potential opportunities for optimization and cost reduction through strategic investments and technology upgrades.

Two promising avenues emerge from this comparison: understanding the discrepancies in radio and tower costs relative to the average values observed in Europe and analyzing the Belgian cost structure to evaluate its potential applicability for the Brazilian context. However, more detailed studies are needed to assess whether and how this cost structure could be adapted to Brazil’s unique conditions. By examining financial models and infrastructure sharing strategies that have been successful in Belgium, we can explore potential insights that can inform strategic planning and the implementation of 5G networks in the southern region of Brazil. This could help enhance coverage and efficiency in both urban and rural settings, though further analysis is required to confirm this applicability.

Although the NHN and network slicing models are primarily analyzed in international contexts such as India and Europe, their applicability to Brazil stems from structural similarities in rural deployment challenges. In Brazil, the vast rural areas, low population densities, and high infrastructure costs mirror the conditions found in countries where the NHN has shown positive outcomes. Furthermore, Brazil’s increasing push for infrastructure sharing and public–private collaboration suggests a favorable environment for implementing such models. Therefore, these international frameworks serve as valuable references for policy design and technical strategy in the Brazilian scenario.

Furthermore, a study from India [13] explores in detail the implementation of an NHN to improve connectivity in rural areas through the cutting of the network.

This approach, in which a single physical network infrastructure is divided into multiple virtual networks, each dedicated to different tenants or services, can be considered in the Brazilian context. Implementing such a model could significantly reduce capital and operational expenditures, making the deployment of 5G in rural areas economically viable. A previous study [12] suggested using clusters for network deployment, where geographic and demographic characteristics dictate the infrastructure requirements. This approach segmented areas based on population density and geographic characteristics, allowing for targeted and efficient network deployment. For Brazil, adopting a similar clustering approach could help us understand the unique cost elements associated with different regions, thus refining financial models to accurately reflect local conditions.

While the cost structure comparison with Belgium highlights significant differences, it is important to recognize that such differences are not solely due to infrastructure or equipment costs. Socioeconomic and geographic conditions—such as labor costs, terrain complexity, and population distribution—play a major role in shaping deployment expenses. Furthermore, regulatory policies, including spectrum allocation mechanisms, taxation on telecommunications equipment, and incentives for infrastructure sharing, differ substantially between Brazil and Belgium. These factors should be considered when evaluating the applicability of European models to the Brazilian context.

5. Conclusions

This study addressed the challenges and opportunities associated with the implementation of 5G technology in the southern region of Brazil, providing valuable information on costs and deployment strategies. The comparative analysis of infrastructure costs between Brazil and Europe revealed discrepancies, with Brazil showing higher tower costs and lower costs for radio equipment and residential CPE.

In Brazil, the regulatory framework for infrastructure sharing is primarily defined by Anatel’s Resolution No. 683/2017 [17], which approves the Regulation for Sharing Support Infrastructure for the Provision of Telecommunications Services. This regulation mandates the sharing of support infrastructure, such as towers and ducts, among service providers, aiming to optimize resource utilization and reduce operational costs. However, practical implementation faces challenges, including bureaucratic hurdles, a lack of enforcement mechanisms, and asymmetries in operator bargaining power. These issues are particularly pronounced in rural areas, where economic incentives are lower and deployment costs are higher. To enhance the feasibility and cost-efficiency of 5G rollouts, it is recommended that regulatory authorities consider expanding incentives for active sharing models and enhancing oversight to ensure compliance. Moreover, the creation of a national infrastructure database—integrating geospatial data and real-time availability—could facilitate the coordination and planning of shared deployments, especially in underserved regions.

The investigation also underscored the potential of the neutral host network (NHN) model, which could offer a cost-effective solution for 5G deployment in rural areas by lowering both CAPEX and OPEX. Furthermore, the cluster-based approach, tailored to population density and geographic characteristics, shows promise for optimizing infrastructure adaptation and resource allocation.

Cost analysis, when integrated into strategic planning, plays a critical role in optimizing both investment allocation and revenue potential in 5G deployments. By quantifying CAPEX and OPEX across different geographic profiles, operators can prioritize regions with higher expected returns or identify where infrastructure sharing models (such as the NHN) may be essential to achieve viability. For instance, in rural areas with low population density and limited economic activity, cost-sharing arrangements can significantly reduce fixed costs, making deployment feasible. In urban centers, the same data can support decisions on densification and the deployment of small cells to maximize spectrum reuse and throughput. Additionally, by aligning cost structures with projected demand and usage patterns, operators can design tailored service offerings that improve customer uptake and revenue generation. Thus, cost assessments not only highlight economic feasibility but also support a targeted, adaptive deployment strategy that enhances overall network profitability.

In conclusion, the successful implementation of 5G in Brazil, especially in the southern region, requires a strategic approach that takes into account regional differences, infrastructure costs, and the regulatory landscape around tower sharing. By adopting efficient cost models and exploring innovative technologies like the NHN, these challenges can be addressed, paving the way for a greater deployment of 5G in urban and rural areas. Future work can build on these findings, tailoring solutions to Brazil’s unique market and infrastructure conditions for a more effective implementation of 5G nationwide.