beam-tracking-ml

What problem does it solve?

This Skill helps translate the RL架構 diagram into modular, reusable code, enforce shape contracts, and design inference-safe ML pipelines for beam tracking tasks.

Core Features & Use Cases

• Modular Architecture: Break down complex beam-tracking ML/RL pipelines into clear components (teacher/student models, observation schemas, and interface layers).
• Inference-Safety & Contracts: Enforce tensor shapes and model interfaces to prevent runtime errors.
• Use Case: Convert a monolithic sionna_beam_tracking script into a clean, testable package with documented interfaces, enabling offline training and predictable online behavior.

Quick Start

Build modular ML/RL components and run an offline evaluation with a sample CSI dataset, following the repo's doc for "plan-impl" and "wire-observation" steps.