Node Importance Assessment for <scp>LLM</scp> ‐Enhanced English Learning and Multilingual Content Distribution in Wireless Networks

ABSTRACT Wireless communication networks increasingly support multilingual content delivery and English learning applications powered by large language models. Current networks struggle to identify critical distribution nodes that balance transmission efficiency with economic value for diverse language content. Nodes serving high‐demand English learning materials or multilingual streaming require different prioritization than standard data traffic. This study proposes LMEN‐MCDI (Large Language Model‐Enhanced Network Multilingual Content Distribution Importance), a method that constructs transmission efficiency matrices to capture both local and global network properties. The approach employs triangular fuzzy logic to build importance evaluation matrices considering content linguistic value and economic factors. Experimental validation demonstrates perfect accuracy matching ground truth values, computation times of 142 milliseconds for 300‐node networks, a 68% reduction over baselines, over 94% accuracy under 20 dB of noise, and stable performance above 93% across varying conditions.