Synthetic Wireless Dataset Supporting: "Integrating Artificial Intelligence into Network Simulation for Enhanced Predictive Analytics

This dataset was developed in support of the research project titled “Integrating Artificial Intelligence into Network Simulation for Enhanced Predictive Analytics.” The project focuses on improving network monitoring and outage prediction by incorporating AI techniques into simulated wireless environments. To facilitate this, synthetic data was generated using MATLAB to model a multi-user wireless network under varying signal conditions and resource constraints.

The simulation captures key communication metrics such as distance from the transmitter, received signal strength (RSSI), signal-to-noise ratio (SNR), and time steps representing different moments in network activity. These variables are intended to reflect realistic fluctuations in signal behavior, making the dataset useful for evaluating predictive analytics models.

Two versions of the dataset are included. The first file, Simulated_WirelessMetrics_Step1 (available in both .csv and .xlsx formats), contains the raw synthetic wireless data without labels. The second file, LabeledWirelessData_Step2, includes the same features as the first but with an added binary label “Outage” that indicates whether a communication failure occurred at a given point. This labeling was based on predefined thresholds for RSSI and SNR and is suitable for supervised learning tasks such as classification or anomaly detection.

The dataset can be used for training and evaluating machine learning models, benchmarking AI-assisted simulations, or exploring how signal conditions impact network performance. Both versions are provided in CSV and Excel formats to accommodate different tools and user preferences.

本数据集为支撑题为“将人工智能（Artificial Intelligence）融入网络仿真以增强预测分析”的研究项目而开发。该项目旨在通过在仿真无线网络环境中集成人工智能技术，提升网络监控与中断预测能力。为推进该研究，研究人员依托MATLAB生成合成数据，以建模不同信号条件与资源约束下的多用户无线网络。

本仿真采集了关键通信指标，包括与发射机的距离、接收信号强度指示（Received Signal Strength Indicator，RSSI）、信噪比（Signal-to-Noise Ratio，SNR）以及表征网络活动不同时刻的时间步长。上述变量旨在反映信号行为的真实波动，使得本数据集可用于评估预测分析模型。

本数据集包含两个版本。第一个文件为Simulated_WirelessMetrics_Step1，支持.csv与.xlsx两种格式，存储无标签的原始合成无线数据。第二个文件为LabeledWirelessData_Step2，与第一个文件包含相同特征，额外新增了二分类标签“Outage”，用于指示指定时刻是否发生通信故障。该标签基于预设的RSSI与SNR阈值生成，适用于分类、异常检测等监督学习任务。

本数据集可用于训练与评估机器学习模型、开展AI辅助仿真的基准测试，以及探究信号条件对网络性能的影响。本数据集的两个版本均提供CSV与Excel格式，以适配不同工具与用户偏好。