AI-Driven Wireless Network Anomaly Detection Dataset
收藏NIAID Data Ecosystem2026-05-02 收录
下载链接：
https://data.mendeley.com/datasets/p4n85smvms
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资源简介：
This dataset is designed for machine learning-based anomaly detection in wireless communication networks. It contains channel measurement data collected from different propagation environments, including Rural Macro (RMa) and Urban Macro (UMa) scenarios with Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) conditions.
Source & Collection Process
Based on 3GPP TR 38.901 standard channel models.
Simulated using QuaDRiGa and real-world propagation conditions.
Feature extraction performed using Space-Alternating Generalized Expectation-Maximization (SAGE).
创建时间：
2025-03-21
