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beam-tracking-ml

@thc1006/beam_tracking_ric_xapp_skeleton
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Design and refactor beam tracking ML/RL pipelines (CSI teacher vs RSRP student), enforce shape contracts, and produce inference-safe models.

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SKILL.md

name beam-tracking-ml
description Design and refactor beam tracking ML/RL pipelines (CSI teacher vs RSRP student), enforce shape contracts, and produce inference-safe models.
allowed-tools Read, Grep, Glob, Bash

Beam Tracking ML Skill

Use this Skill when:

  • translating the RL架構 diagram into code
  • refactoring sionna_beam_tracking_v2.py ideas into modular components
  • designing observation/action schemas

Guardrails

  • Always define and test shapes (B,N_BEAMS) etc.
  • Keep student (online) policy lightweight and deterministic.
  • Treat CSI-heavy path as offline only unless we explicitly design compression.

Where to put code

  • Models: beam_tracking/model/
  • Training scripts: scripts/ (do not bloat runtime xApp)
  • Interfaces: beam_tracking/schemas.py

Suggested distillation workflow

  1. Train teacher on CSI dataset (offline).
  2. Run teacher over same trajectories, log action distributions.
  3. Train student to match teacher (KL divergence).
  4. Optionally fine-tune student with small online data.