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Analysis of crowdsourced data for estimating data speeds across service areas of India

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Abstract

The intense adoption of Information Technology by businesses and government have increased data consumption across the world. While some countries have augmented their telecom infrastructure, data speeds are still very low in countries such as India. In this paper, we collected about 25 million records of crowdsourced data obtained through the mobile app deployed by the regulator in India. We have built a panel data regression model and analyzed the effect of supply-side variables such as radio spectrum holding of the operator, the mobile access infrastructure deployed by the operators, the technology deployed (3G/4G), and the demand side variable such as the mobile subscriber base. Our analysis indicates that a lower amount of spectrum holding, poor receive signal strength at mobile handsets, and the technology deployed (3G/4G) negatively affect the users’ download data speeds. The subscriber base also has a moderate effect on the data speeds. We conclude by prescribing policy recommendations on spectrum allocation and improvements in mobile access technologies to augment users’ quality of experience.

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Appendices

Appendix 1: Variation of total subscribes across different service areas of India. Source: Author’s own

figure d

Appendix 2: Variation in spectrum holding (in MHz) of an operator across service areas

figure e

Appendix 3: Variation of subscribers of an operator across different service areas of India. Source: Author’s own

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Sridhar, V., Girish, K. & Badrinarayan, M. Analysis of crowdsourced data for estimating data speeds across service areas of India. Telecommun Syst 76, 579–594 (2021). https://doi.org/10.1007/s11235-020-00736-z

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