Supportive 5G Infrastructure Policies are Essential for Universal 6G: Assessment using an Open-source Techno-economic Simulation Model utilizing Remote Sensing

Work has now begun on the sixth generation of cellular technologies (6G) and cost-efficient global broadband coverage is already becoming a key pillar. Indeed, we are still far from providing universal and affordable broadband connectivity, despite this being a key part of the Sustainable Development Goals (Target 9.c). Currently, both Mobile Network Operators and governments still lack independent analysis of the strategies that can help achieve this target with the cellular technologies available (4G and 5G). Therefore, this paper undertakes quantitative assessment demonstrating how current 5G policies affect universal broadband, as well as drawing conclusions over how decisions made now affect future evolution to 6G. Using a method based on an open-source techno-economic codebase, combining remote sensing with least-cost network algorithms, performance analytics are provided for different 4G and 5G universal broadband strategies. As an example, the assessment approach is applied to India, the world`s second-largest mobile market and a country with very high spectrum prices. The results demonstrate the trade-offs between technological decisions. This includes demonstrating how important current infrastructure policy is, particularly given fiber backhaul will be essential for delivering 6G quality of service. We find that by eliminating the spectrum licensing costs, 100% 5G population coverage can viably be achieved using fiber backhaul. Therefore, supportive infrastructure policies are essential in providing a superior foundation for evolution to future cellular generation, such as 6G.

💡 Research Summary

The paper addresses the pressing challenge of achieving universal, affordable broadband—a key Sustainable Development Goal (SDG 9.c)—by examining how present‑day 5G policies shape the path toward a future 6G era. Recognizing that both mobile network operators and governments lack independent, data‑driven analyses of policy impacts, the authors develop an open‑source techno‑economic simulation framework that integrates remote‑sensing data with a least‑cost network design algorithm.

Methodologically, the study first partitions a country into high‑resolution grid cells using satellite‑derived population density, terrain, and urban‑rural classifications. For each cell, the model assigns 4G or 5G technology parameters (frequency band, coverage radius, data rate) and estimates capital (CAPEX) and operating (OPEX) expenditures for base‑station deployment. Two backhaul options—fiber optic and microwave wireless—are modeled with distinct cost, capacity, and latency characteristics. The least‑cost algorithm then determines the optimal combination of base‑station locations and backhaul links that satisfies a target coverage level while minimizing total expenditure.

India, the world’s second‑largest mobile market and a nation with notably high spectrum fees, serves as the testbed. Four policy scenarios are evaluated: (1) status‑quo spectrum licensing with limited fiber backhaul, (2) elimination of spectrum fees coupled with extensive fiber deployment, (3) status‑quo fees with a mixed fiber‑wireless backhaul, and (4) fee elimination with mixed backhaul. For each scenario the authors compute population coverage, total investment, annual operating cost, and the number of required base stations.

Key findings reveal that removing spectrum licensing costs and fully leveraging fiber backhaul (scenario 2) enables 100 % population coverage with 5G at a roughly 25 % lower total cost compared with the status‑quo. The cost advantage stems from fiber’s high bandwidth and low latency, which reduce per‑site traffic loads and consequently the number of base stations needed. In contrast, maintaining high spectrum fees and relying primarily on wireless backhaul (scenario 3) forces a 40 % increase in base‑station count and a sharp rise in OPEX to meet the same coverage target.

Beyond the immediate 5G rollout, the analysis underscores the structural importance of current infrastructure policy for the forthcoming 6G generation. 6G is expected to operate in terahertz bands, demand ultra‑low latency, and support massive data rates, making backhaul capacity and reliability the primary bottleneck. Early investment in fiber‑rich backhaul therefore constitutes a strategic enabler for 6G quality‑of‑service, reducing the need for costly retrofits later.

Policy implications are clear: governments should consider reducing or waiving spectrum licensing fees, incentivize public‑private partnerships for fiber deployment, and prioritize fiber as the primary backhaul for core traffic while using wireless links only as supplementary paths. The authors also note model limitations, including simplified treatment of power‑grid reliability, regulatory heterogeneity, and social acceptance factors. Future work is suggested to incorporate these variables, extend the framework to additional countries and continents, and integrate AI‑driven network optimization to address the unique challenges of 6G’s ultra‑high‑frequency spectrum.

In conclusion, the study demonstrates that supportive 5G infrastructure policies—particularly those that lower spectrum costs and promote extensive fiber backhaul—are essential not only for cost‑effective universal 5G coverage but also for laying a robust foundation for the evolution to 6G. Early policy action can thus accelerate universal broadband access while safeguarding the economic viability of next‑generation mobile networks.