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Poster: Estimating Cell Load from End-user Crowdsourced Measurements in a Real-world Cellular Network

Published: 04 November 2024 Publication History

Abstract

Optimizing mobile networks in the rapidly evolving field of wireless communication is increasingly challenging due to two main issues associated with current methods. First, the technical complexity of the Radio Access Network (RAN) with multiple technologies, frequency bands, and cell sizes makes it difficult for manual processing to keep pace with the growing number of issues to be resolved. Second, network optimization usually focuses on data gathered by network equipment, i.e. base stations, and overlooks user-side information, which can offer data with better spatial precision and more accurate Quality of Service (QoS) as seen by the end user.
One of the main problems for alternative mobile network optimization methods that exploit user-related information is that they also require network-related knowledge, such as the deployed infrastructure and network load, which may not be available. However, network quality measurements at the User Equipment (UE), such as Reference Signal Received Quality (RSRQ) in LTE networks, contain information about the total power received in the entire cell bandwidth, from which a proxy for cell load may be derived. In this work, we propose a generalized method to derive cell load from RSRQ, and test it in a commercial mobile network using crowdsourced measurements.

References

[1]
Mah-Rukh Fida and Mahesh K Marina. Uncovering mobile infrastructure in developing countries with crowdsourced measurements. In Proceedings of the Tenth International Conference on Information and Communication Technologies and Development, pages 1--11, 2019.
[2]
Mahesh K Marina, Valentin Radu, and Konstantinos Balampekos. Impact of indoor outdoor context on crowdsourcing based mobile coverage analysis. In Proceedings of the 5th Workshop on All Things Cellular: Operations, Applications and Challenges, pages 45--50, 2015.
[3]
Franceso Malandrino, Scott Kirkpatrick, and Danny Bickson. What is LTE actually used for? an answer through multi-operator, crowd-sourced measurement., 2016.
[4]
Zoraida Frias, Luis Mendo, and Edward J. Oughton. How does spectrum affect mobile network deployments? empirical analysis using crowdsourced big data. IEEE Access, 8:190812--190821, 2020.
[5]
Rohde & Schwarz. Qualipoc Android. https://www.rohde-schwarz.com/us/products/test-and-measurement/network-data-collection/qualipocandroid_63493--55430.html. [Online; accessed 14-May-2024].

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  1. Poster: Estimating Cell Load from End-user Crowdsourced Measurements in a Real-world Cellular Network

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      cover image ACM Conferences
      IMC '24: Proceedings of the 2024 ACM on Internet Measurement Conference
      November 2024
      812 pages
      ISBN:9798400705922
      DOI:10.1145/3646547
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      New York, NY, United States

      Publication History

      Published: 04 November 2024

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      Author Tags

      1. cell load
      2. crowdsourced measurements
      3. lte
      4. reference signal received power
      5. reference signal received quality

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      • Ministry of Science, Innovation and Universities of Spain

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      IMC '24
      IMC '24: ACM Internet Measurement Conference
      November 4 - 6, 2024
      Madrid, Spain

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      Overall Acceptance Rate 277 of 1,083 submissions, 26%

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