"LTEv2xMode4Dataset"

"The LTE-V2X Mode 4 Dataset comprises 1,156,676 high-fidelity samples derived from a 3GPP-compliant analytical model. It captures sidelink communication dynamics by mapping five inputs\u2014transmission power (Pt\u200b), subchannels (S), vehicle density (\u03b2), packet frequency (\u03bb), and distance (d)\u2014to performance metrics. Specifically, it provides the Packet Delivery Ratio (PDR) and four error probabilities: half-duplex, detection, propagation, and collision. This extensive volume facilitates training MTL-DNN models for real-time, prescriptive resource optimization. The data enables transitioning from reactive to cognitive management, ensuring reliability in high-density vehicular environments.Instructions for UtilizationRequired Libraries: To process the dataset for AI training, we recommend using Python with the following libraries: pandas, numpy, scikit-learn, and tensorflow or keras.Data Normalization: Given the different scales of input features (e.g., distance up to 500 vs. density at 0.05), StandardScaler (Z-score normalization) must be applied to the input vector to ensure stable convergence."