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AI-based Intelligent Parameter Optimization Scheme for Preventing Cell Overload in Massive IoT Environments

  • Journal of Internet of Things and Convergence
  • Abbr : JKIOTS
  • 2026, 12(5), 1
  • Publisher : The Korea Internet of Things Society
  • Research Area : Engineering > Computer Science > Internet Information Processing
  • Received : June 1, 2026
  • Accepted : August 19, 2026
  • Published : October 31, 2026

Bok-Nyong Park 1,  June-Hyuk Kwon 1

1LG유플러스

Accredited

ABSTRACT

With the recent rapid proliferation of IoT devices, massive connectivity based on IoT network (LTE Cat.M1, NB-IoT and so on) is becoming increasingly frequent. In particular, when a large number of devices attempt to connect simultaneously, Radio Resource Control (RRC) connection resources within the base station become exhausted, leading to overload conditions that block new device access. To address this issue, this paper proposes an AI-based intelligent Inactivity Timer optimization algorithm. To overcome the rigidity of conventional fixed-threshold methods, the proposed algorithm mathematically defines the relationship between base station resource availability and Quality of Service (e.g., drop rate) and optimizes system weights in real-time using a Deep Q-Network (DQN). Performance evaluation results demonstrate that the proposed AI-based intelligent hybrid control model enhances capacity compared to existing fixed and rule-based methods in massive IoT environments.

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