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BISCAY: Practical Radio KPI Driven Congestion Control for Mobile Networks

Authors Jon Larrea , Tanya Shreedhar , Atte Niemi, Adel Sefiane , Mahesh K. Marina

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Subject Classification

ACM Subject Classification
  • Networks → Mobile networks
  • Networks → Transport protocols
  • Networks → Network resources allocation
Keywords
  • Cellular Networks
  • Congestion Control
  • LTE/5G

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Abstract

Mobile application performance is often bottlenecked by cellular links with rapid bandwidth fluctuations. We show that radio KPIs from the device chipset can precisely and promptly measure available cellular bandwidth. Building on this, we propose Biscay, a practical KPI-driven congestion control for mobile networks. Biscay leverages OpenDiag, an in-kernel, real-time KPI extractor we introduce along with a KPI-based bandwidth estimator to adjust the congestion window, utilizing available bandwidth while minimizing delay. We implement Biscay and OpenDiag on unrooted Android 5G phones. Across trace-driven emulations and real-world 4G/5G experiments, Biscay outperforms state-of-the-art CCAs (e.g., BBR, CUBIC), typically reducing average and tail delay by >90% while matching or improving throughput. These gains stem from OpenDiag’s 100× finer on-device KPI granularity than existing alternatives like MobileInsight.

Cite As Get BibTex

Jon Larrea, Tanya Shreedhar, Atte Niemi, Adel Sefiane, and Mahesh K. Marina. BISCAY: Practical Radio KPI Driven Congestion Control for Mobile Networks. In 1st New Ideas in Networked Systems (NINeS 2026). Open Access Series in Informatics (OASIcs), Volume 139, pp. 15:1-15:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/OASIcs.NINeS.2026.15

Author Details

Jon Larrea
  • Revelare Networks, Pikesville, MD, USA
Tanya Shreedhar
  • Networked Systems group, TU Delft, The Netherlands
Atte Niemi
  • Informatics, University of Edinburgh, UK
Adel Sefiane
  • Imperial College London, UK
  • NVIDIA, London, UK
Mahesh K. Marina
  • Informatics, University of Edinburgh, UK

Acknowledgements

I want to thank Aita.

Supplementary Materials

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