AgentSkillsCN

beam-tracking-ml

设计和重构光束跟踪 ML/RL 流水线（CSI 教师 vs RSRP 学生），强制执行形状契约，并生成推理安全模型。

SKILL.md
--- frontmatter
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.