Introduction

Failures in 5G mobile networks are becoming the norm with the ongoing global rollout. If left unattended, they affect mobile user experiences and the proper functioning of applications. In this work, we describe SEED, which offers a novel SIM-based solution to 5G failure diagnosis and handling. SEED infers failure causes by exploiting current standardized 5G error codes and decision-tree/online learning algorithms. It further takes corresponding multi-tier reset/redo actions (reset protocol operations, refresh outdated configurations, reload profiles, etc.) once the failure cause is inferred. SEED takes the operator's perspective in its design for fast deployment. SEED design works within the 5G standard framework and does not require changes on the device firmware or infrastructure hardware. Our evaluation has confirmed the viability of SEED.

Team Member

• Boyan Ding  (University of California, Los Angeles)
• Jinghao Zhao  (University of California, Los Angeles)
• Zhaowei Tan  (University of California, Los Angeles)
• Yifei Xu  (University of California, Los Angeles)
• Songwu Lu  (University of California, Los Angeles)

Publications

Code Release