Optimizing Network Costs for NFV Solutions in Urban and Rural Indian Cellular Networks

With the rapid growth of telecommunication infrastructure in India, there is a need for smarter, more innovative solutions to meet the demands of infrastructure expansion while keeping the costs optimized. Using Network Function Virtualization (NFV) promises a significant reduction in operation and setup costs. This paper aims to evaluate the economic impact of NFV implementation in urban and rural Indian contexts. The study conducts a thorough cost benefit analysis to assess the advantages of NFV adoption for Indian telecom operators, businesses and lawmakers. The research uses case studies to examine existing NFV implementations in India. In both the urban and rural contexts, the emphasis is on cost-saving, cost-effectiveness, services, quality of services, user satisfaction and coverage. Comparisons across all these scenarios are identified to understand the drivers and barriers to NFV adoption in India. Insight is offered into the impact of policies and the state of the existing technological infrastructure. The findings reveal that NFV can significantly optimized network costs and help improve service quality while providing a favorable return to investors within the calculated payback period. Additionally, best practices for effective NFV deployment are mentioned providing guidelines for telecom operators and businesses. This paper contributes to the general understanding of NFV as a potential tool to transform existing telecommunications infrastructure in India, emphasizing its impact via network efficiency and improvements in quality of service.

Introduction

Indian smartphone penetration stands at 70.95% as of 2023 and is expected to reach close to 90% by 2030 [1]. The rapid increase in smartphone adoption and the spread of affordable data plans have led to a large increase in data consumption among users. Smartphone usage has become quite ubiquitous for all aspects of life and is used by every strata of society for day-to-day activities such as banking, shopping and social networking [2]. This makes continuous improvement and expansion of the telecom infrastructure necessary to meet the growing demand for all kinds of user services.

Based on a PriceWaterCooper House study, the Indian telecom market is highly competitive with over 10 key players [3], [4]. With the rapid development and growth of technology, telecom companies are focused on maximizing profits given the nature of competition within the telecom sector [5]. The expansion of cellular networks into both urban and rural areas in India is blocked by many obstacles. Urban areas are characterized by high population density which often results in network congestion [6]. This network congestion can lead to reduced bandwidth available for a large number of users resulting in poor quality of service for all users. Urban areas are also facing a spectrum shortage due to the large number of devices that are using the available cellular spectrum [7]. All telecom operators are fighting for the same scarce resources which makes optimization and efficient utilization of paramount importance. High-rise buildings and the vast network of multi-laned roads can also be barriers to the expansion of cellular networks. There are high operating and maintenance costs of telecommunication infrastructure in urban cities stemming from costs of real estate, costs for towers and equipment and labor. Rural areas have the opposite problem where the very sparse population makes it unviable to set up cellular network infrastructure since the return on investment in these areas can be lower. Rural areas are generally underdeveloped due to the nature of terrain which can be mountainous, rugged or inaccessible. These factors make the setup of infrastructure unfeasible due to logistical costs. People in rural areas also are on the lower bands of the economic strata and telecom operators need to reduce operating margins to sell mobile plans which makes it less attractive. There is a general lack of facilities such as electricity and internet in rural areas which makes setup of cellular towers harder.

Network function virtualization (NFV) reforms the way network architecture is set up by leveraging virtualization to separate hardware and software by ensuring network functions are implementable across a common pool of hardware [8]. By decoupling network functions from the hardware, network operators can develop, use and run services independent of the hardware thus reducing setup costs. For instance, the core cellular networks can be implemented via NFV using software-defined mobile networks [9]. NFV offers many opportunities for revenue and other economic value addition in the services value chain [10]. NFV is a crucial technique via which operators can quickly scale and deploy network infrastructure in both urban and rural communities. By separating software from hardware, developers can focus exclusively on the software aspect of cellular networking thus increasing the pace of development and this can be quickly deployed by operators as needed. This is key to improving aspects of the quality of service.

In urban areas of India, NFV can help scale networks with the increasing number of user base by deploying more hardware. This will help prevent the drop in quality of service and avoid network congestion [11]. Load balancing is a key change with NFV in urban areas that can help distribute network traffic across nodes [12]. In rural areas, network operators can leverage existing hardware to deploy software services in remote inaccessible areas thereby avoiding higher logistical costs. Based on the local demands of the rural areas, telecom operators can provide the appropriate service plans by using NFV to customize the software functions. With government programs such as Digital India and BharatNet, NFV can enable a cost-effective way to expand digital connectivity across India.

The remainder of this paper is structured as follows: Section 2 reviews existing literature on NFV, focusing on its benefits and challenges. Section 3 details the research methodology, including data collection, case study selection, and the analytical framework for cost-benefit analysis. Section 4 presents the key results and findings from the cost-benefit analysis research. Section 5 presents future work to address the deficiencies of this research study and finally section 6 offers the conclusion of the paper with key findings.

Related Works

Li et al. proposed a dynamic and cost-efficient edge resource management platform for NFV networks [13]. Experiments were conducted to figure out the effect of NF resource allocation and assign the appropriate CPU cores to improve cost efficiency. Based on the evaluations, it was determined that Finedge can handle resource allocation with the lowest CPU quota and highest SLA satisfaction rate compared to the traditional OS scheduler or other state-of-the-art resource management techniques.

Hernandez-Valencia et al. show the operational costs involved for a traditional service provider and provide details on how NFV methods can be used to influence business policies [14]. With Software Defined Networking (SDN) and NFC as some of the more vital components for network service providers, one of the main benefits is the reduction of operational costs using network programmability and automating operational execution. The study provides the drivers of operation expenditure changes, the direction of the changes and the categories of operation expenditures that will be affected are presented.

Wang and Hu have examined the converged Radio Access Network (RAN) and Mobile Edge Computing (MEG) for 5G deployment [15]. In their study, they investigated and characterized the load on commercial off-the-shelf edge platforms and analyzed the costs between traditional RAN against virtual RAN. With a virtual RAN system, there will be benefits for the future edge NFV design.

Sairam et al. proposed a lightweight architecture for Virtualized Network Function (VNF) to deploy security for Internet of Things (IoT) applications named NETRA [16]. With the increasing threat of cyber criminals in the modern connected world, it is essential to monitor smart devices closer to their real location which is at the edge of the IoT network. The paper explored how these security features can be implemented at the edge of the network in order to provide security. The performance of this proposed NFV-based security tool was done to show that attacks can be detected with more than 95% accuracy in less than one second.

Methodology

Fig. 1 illustrates the system used in this paper for the cost benefit analysis for a telecom operator network setup. To assess the cost savings opportunity from NFV, the first step is to analyze the current cost structure for a telecom operator. This will involve finding out all the cost categories mainly capital expenditures (CAPEX) for network equipment, operating expenses (OPEX) for maintenance, power and labor and other costs.

Fig. 1. Network function virtualization.

Next, for each major cost category, the potential benefits by implementing NFV should be estimated. For example, NFV may enable a 20% reduction in maintenance costs or a 25% decrease in network equipment CAPEX.

These savings can then be applied to the operator’s current costs in each category to calculate the total savings. Summing the savings across all applicable categories will provide the total potential annual cost reduction from implementing NFV. This process of identifying the cost-benefit has been illustrated via a flowchart in Fig. 2.

Fig. 2. Flowchart for cost benefit analysis on Telecom operator network setup.

Gadi et al. give a very detailed breakdown of the costs associated with setting up a GSM base station in India [17]. Telecom operators in India follow a manual setup procedure to set up cellular base stations. Base stations consist of a ground-based steel tower that contains a battery and is powered by a diesel generator. This study was performed in 2014 and the inflation in India since 2014 per year is 4.9%, 4.53%, 3.6%, 3.4%, 4.7%, 6.2%, 5.5%, 6.65%, 4.38%, 4.56% [18]. This comes to a cumulative inflation rate of around 46%. For the purposes of easier calculation, this will be considered at around 50%. Using this cumulative inflation rate, costs for setting up a GSM base station are listed in Table I. Based on the calculations with adjusted inflation, the total cost for setting up a base station along with the relevant supporting infrastructure comes to INR 6.67 million.

Table I. GSM Base Tower Setup Costs

Cost category	Cost in INR
Rent	28,0000
Operating cost	2,346,000
40-meter ground based steel tower	1,500,000
Battery/power plan & civil work	600,000
Diesel generator engine	450,000
Base Transceiver Station (BTS)	1,500,000
Total	6,676,000

Based on research in [19], it is estimated to cost around INR 15,350 million–18,760 million per 1 MHz of pan-India spectrum. Other key costs include maintenance, rent, backhaul, security, and regulatory fees which together can account for 15%–25% of total operating expenses. Table II lists all the costs associated with a new network setup from an operator’s perspective. From Table I, the relevant costs are included to calculate the total cost of setting up a network. For purposes of simplicity, the operating cost from Table I will be considered as INR 2.5 million.

Table II. Complete Cost of a New Network Setup for Indian Operators

Cost category	Cost in million INR
Spectrum fees	17,000
Network equipment	2000
Maintenance and repairs	750
Backhaul connectivity	5
Security and monitoring	250
Regulatory fees and taxes	750
IT equipment and servers	5000
Power and cooling	1000
Operating cost	2.5
Total	26,757.5

This data is based on certain important factors. Security and monitoring costs are estimated to be 2%–3% of total operating expenses for a large telecom operator [20]. For an operator with ₹10,000 million annual Opex, this would equate to ₹200 million–₹300 million per year. Regulatory fees and taxes are estimated at 5%–10% of revenue [20]. For an operator with ₹10,000 million in annual revenue, this would be ₹500 million–₹1,000 million per year. The other cost categories include fiber backhaul costs ranging from ₹1 million to ₹10 million per km [20], [21]. While spectrum fees are by far the largest cost item, security/monitoring and regulatory fees can also add up to hundreds of millions of INR annually for a large telecom operator in India. Fiber backhauls is a major capex investment but essential for future-proofing networks.

For the purposes of this study, spectrum fees are assumed to be the midpoint of the provided range. Maintenance and repairs are assumed to be 7.5% of Opex, the midpoint of the 5%–10% range. Fiber backhaul costs are assumed at an average cost of ₹5 million per km. Security and monitoring costs are assumed at 2.5% of Opex, the midpoint of the 2%–3% range. Regulatory fees are assumed at 7.5% of revenue, the midpoint of the 5%–10% range.

Cost Savings with NFV

NFV methodologies adds great value by introducing cost savings for telecom operators. Reduced Hardware Costs are a big advantage of implementing NFV since now telecom operators can use common hardware rather than expensive specialized hardware meant for individual applications. A study cited by Light Reading found that NFV can enable cost savings of nearly 70% [22]. Here, NFV allows operators to bank on the fast pace of innovation and economies of scale in the server industry instead of being forced to depend on a specific variety of proprietary hardware vendors. Traditionally telecom networks are designed and engineered to handle peak loads which makes them inefficient and results in underutilization of the available resources. With the advent of NFV, it enables operators to rely on dynamically scaling the use of network hardware resources to meet the increasing real-time demand. There is evidence of reducing costs by 24% by deploying a larger NFV deployment which helps in optimizing resource usage. The initial setup of software investment in R&D might be higher, however, the savings from hardware, installation configuration and power savings help offset these extra setup costs.

A study by Rokkas et al. found that using fewer physical servers based on multiple network functions consolidation via the implementation of NFV reduces the space, power and cooling requirements compared to traditional hardware-based networks [23]. A reduction of 26% in the Total Cost of Ownership (TCO) was found to be possible by increasing the power density and size of data centers. However, there are diminishing returns after an optimal point.

Given this context, the savings in setting up a cellular network can be calculated for individual line cost items.

From Table III it is evident that implementing NFV solutions for telecom operators can yield significant savings. From column 4 the total cost with NFV solutions comes to a total of ₹24,066.85 million against the original total cost of ₹26,757.5 million. Subtracting the new cost from the original cost results in a total savings of ₹2690.65 million. This represents a total savings of 10.05% which is a significant savings.

Table III. Original vs. Cost Savings for Network Setup with NFV

Cost item	Original cost(in million INR)	Estimated cost savings	New cost(in million INR)
Spectrum fees	17,000	No savings	17,000
Maintenance & repairs	750	No savings	750
Backhaul connectivity	5	No savings	5
Security & monitoring	250	No savings	250
Regulatory fees and taxes	750	No savings	250
IT equipment (servers)	5000	24%	3800
Network equipment (switches, routers)	2000	24%	1520
Power and cooling	1000	26%	740
Operating cost	2.5	26%	1.85
Total	26,757.5		24,066.85

Results and Discussions

From earlier calculations, a telecom operator can achieve savings of nearly 10% for every new setup. This is a crucial saving since with the growing need for capacity expansion, telecom operators need to keep expanding their network setup at a fast pace. For an operator which has nearly 100 new setups in a year, this amounts to a total saving of INR 200 billion annually. NFV, with the utilization of common hardware, automation and centralized control, enables major savings in both capital and operating expenses. Based on the study in this paper, NFV can potentially reduce an operator’s Total Cost of Ownership (TCO) by around 10%, with the largest savings coming from 24%–26% reductions in CAPEX on network equipment and OPEX on power, cooling and maintenance.

Future Work

To further the findings of this paper, future research must be conducted that focuses on gathering actual cost data and percentage savings from Indian telecom operators that have implemented NFV. Case studies of successful deployments would provide valuable insights into the specific challenges, best practices and realized benefits.

Additionally, along with the integration of NFV, the future work can include emerging technologies like 5G, edge computing and network slicing to name a few. Indian operators will benefit from their understanding of how NFV can be used to optimize next-generation network setup and help maintain a competitive edge in the competitive telecom market of India.

Further analysis is needed on the non-financial benefits of NFV such as its impact on user experience, service quality, and network reliability and robustness. If these qualitative factors can be quantified with real numbers that will also help strengthen the business case for NFV adoption.

Conclusions

The analysis presented in this paper demonstrates that Network Functions Virtualization (NFV) can deliver significant cost savings and operational efficiency improvements for Indian telecom operators. With NFV’s capability to utilized automation and centralized control, operators can save on both capital and operating expenses while enhancing their customer user experience.

The paper deduced savings that potentially lower an operator’s Total Cost of Ownership (TCO) by around 10% with major savings in CAPEX at around 24% on network equipment and 26% savings in OPEX on power, cooling and maintenance.

NFV also provides substantial operational efficiency along with immediate savings on costs. Operating expenses can be lowered via automation and centralized control that improve network reliability and reduce the possibility of manual errors. Flexible bandwidth requirements can also be met to satisfy the varying customer on-demand requirements. The exact savings from implementing NFV will only depend on the operator’s specific approach to network setup processes and cost structure. The potential benefits this paper outlines make a very strong business case for NFV adoption in this context.

The adoption of NFV in India has been slower compared to other markets, especially China and the USA. In order for telecom operators in India to remain competitive and meet the demand for high-speed and low-latency data, it is crucial to take up this modern new technology. Those who do are going to be well-positioned to monetize on new services and achieve significant cost savings further down the line as 5G rolls out.