Capacity Optimization in NB-IoT Networks Using Genetic Algorithm-Based Device Grouping

Abstract

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The rapid growth of Internet of Things (IoT) devices has increased the demand on cellular networks, particularly within Narrowband Internet of Things (NB-IoT) technology. To address the challenge of limited cellular capacity, this paper proposes an optimization method that groups devices and allocates specific time slots for each group to engage with the base station. The aim is to minimize interference and packet collisions, ensuring efficient device connectivity. We explore various clustering algorithms, including K-means, uniform repetition, and genetic algorithms (GA), with a focus on GA for its superior performance in reducing interference and improving connection success rates. Simulations confirm that the GA-based approach effectively manages device groups, enhances connectivity, and optimizes cell capacity in NB-IoT networks.